This position is located in Bengaluru As part of the AWS Solutions organization, we have a vision to provide business applications, leveraging Amazon's unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers' businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazon's real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use. With Just Walk Out (JWO), our mission is to build the future of physical retail in collaboration with Amazon Go and Fresh Stores, in addition to stadiums, airports, healthcare facilities and university campuses looking to increase throughput, extend operating hours and improve efficiency. In addition we have conviction that visual understanding and reasoning can be applied in multiple new ways to manage physical spaces. The Role In this role, you will apply advanced analysis technique and statistical concepts to draw insights from massive datasets, create intuitive data visualizations, and build scalable machine learning models. You are a pragmatic generalist. You can contribute to each layers of a data solution - you work closely with business intelligence engineers, data engineers and product managers to obtain relevant datasets and prototype predictive analytic models, you team up with data engineers and software development engineers to implement data pipeline to productionize your models, and review key results with business leaders and stakeholders. Your work exhibits a balance between scientific validity and business practicality. To be successful in this role, you must be able to turn ambiguous business questions into clearly defined problems, develop quantifiable metrics and robust machine learning models from imperfect data sources, and deliver results that meet high standards of data quality, security, and privacy. 1. Define and conduct experiments to optimize JWO shopping experience and inquires, and communicate insights and recommendations to product, engineering, and business teams 2. Interview stakeholders to gather business requirements and translate them into concrete requirement for data science projects 3. Build models that forecast growth and incorporate inputs from product, engineering, finance and marketing partners 4. Define metrics and design algorithms to estimate customer satisfaction and engagement in real-time 5. Apply data science techniques to automatically identify trends, patterns, and frictions of customer interaction and retention 6. Work with data engineers and software development engineers to deploy models and experiments to production 7. Identify and recommend opportunities to automate systems, tools, and processes. Key job responsibilities 1. Build and maintain time series forecasting models for demand planning using advanced forecasting tools and Python. 2. Design and build simulators and automated processes for shift planning and other organizational needs. 3. Define and evaluate key business metrics to drive decision-making and strategy. 4. Develop machine learning tools to enhance operational efficiency and human-in-the-loop processes. 5. Conduct anomaly detection and predictive analysis to forecast hardware failures and maintain operational continuity. 6. Leverage sampling methods and uncertainty analysis to evaluate associate performance accurately and cost-effectively. 7. Conduct experiments, including A/B tests, to support business decisions and model development. 8. Stay up to date with developments in generative AI, incorporating latest techniques into tools and models. 9. Develop statistical models to evaluate current systems and identify optimization opportunities. 10. Work autonomously and manage projects with little oversight, driving them from inception to implementation. 11. Regularly write up your work and findings in internal doc reviews About the team Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. Why AWS Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve. Inclusive Team Culture AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. Mentorship and Career Growth We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. - 2+ years of data scientist experience - 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience - 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience - Experience applying theoretical models in an applied environment - Experience in Python, Perl, or another scripting language - Experience in a ML or data scientist role with a large technology company Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.
Jun 27, 2025
Full time
This position is located in Bengaluru As part of the AWS Solutions organization, we have a vision to provide business applications, leveraging Amazon's unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers' businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazon's real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use. With Just Walk Out (JWO), our mission is to build the future of physical retail in collaboration with Amazon Go and Fresh Stores, in addition to stadiums, airports, healthcare facilities and university campuses looking to increase throughput, extend operating hours and improve efficiency. In addition we have conviction that visual understanding and reasoning can be applied in multiple new ways to manage physical spaces. The Role In this role, you will apply advanced analysis technique and statistical concepts to draw insights from massive datasets, create intuitive data visualizations, and build scalable machine learning models. You are a pragmatic generalist. You can contribute to each layers of a data solution - you work closely with business intelligence engineers, data engineers and product managers to obtain relevant datasets and prototype predictive analytic models, you team up with data engineers and software development engineers to implement data pipeline to productionize your models, and review key results with business leaders and stakeholders. Your work exhibits a balance between scientific validity and business practicality. To be successful in this role, you must be able to turn ambiguous business questions into clearly defined problems, develop quantifiable metrics and robust machine learning models from imperfect data sources, and deliver results that meet high standards of data quality, security, and privacy. 1. Define and conduct experiments to optimize JWO shopping experience and inquires, and communicate insights and recommendations to product, engineering, and business teams 2. Interview stakeholders to gather business requirements and translate them into concrete requirement for data science projects 3. Build models that forecast growth and incorporate inputs from product, engineering, finance and marketing partners 4. Define metrics and design algorithms to estimate customer satisfaction and engagement in real-time 5. Apply data science techniques to automatically identify trends, patterns, and frictions of customer interaction and retention 6. Work with data engineers and software development engineers to deploy models and experiments to production 7. Identify and recommend opportunities to automate systems, tools, and processes. Key job responsibilities 1. Build and maintain time series forecasting models for demand planning using advanced forecasting tools and Python. 2. Design and build simulators and automated processes for shift planning and other organizational needs. 3. Define and evaluate key business metrics to drive decision-making and strategy. 4. Develop machine learning tools to enhance operational efficiency and human-in-the-loop processes. 5. Conduct anomaly detection and predictive analysis to forecast hardware failures and maintain operational continuity. 6. Leverage sampling methods and uncertainty analysis to evaluate associate performance accurately and cost-effectively. 7. Conduct experiments, including A/B tests, to support business decisions and model development. 8. Stay up to date with developments in generative AI, incorporating latest techniques into tools and models. 9. Develop statistical models to evaluate current systems and identify optimization opportunities. 10. Work autonomously and manage projects with little oversight, driving them from inception to implementation. 11. Regularly write up your work and findings in internal doc reviews About the team Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. Why AWS Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve. Inclusive Team Culture AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. Mentorship and Career Growth We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. - 2+ years of data scientist experience - 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience - 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience - Experience applying theoretical models in an applied environment - Experience in Python, Perl, or another scripting language - Experience in a ML or data scientist role with a large technology company Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.
Business Research Analyst - II, RBS Tech As a Research Analyst, you'll collaborate with experts to develop cutting-edge ML and Gen AI/LLM solutions for business needs. You'll drive product pilots, demonstrating innovative thinking and customer focus. You'll build scalable solutions, write high-quality code, and develop state-of-the-art ML models. You'll coordinate between science and software teams, optimizing solutions. The role requires thriving in ambiguous, fast-paced environments and working independently with ML models. Key job responsibilities • Collaborate with seasoned Applied Scientists and propose best in class ML solutions for business requirements • Dive deep to drive product pilots, demonstrate think big and customer obsession LPs to steer the product roadmap • Build scalable solutions in partnership with Applied Scientists by developing technical intuition to write high quality code and develop state of the art ML models utilizing most recent research breakthroughs in academia and industry • Coordinate design efforts between Sciences and Software teams to deliver optimized solutions • Ability to thrive in an ambiguous, uncertain and fast moving ML usecase developments. • Familiar with ML models and work independent. • Mentor Junior Research Analyst (RAs) and contribute to RA hiring About the team Retail Business Services Technology (RBS Tech) team develops the systems and science to accelerate Amazon's flywheel. The team drives three core themes: 1) Find and Fix all customer and selling partner experience (CX and SPX) defects using technology, 2) Generate comprehensive insights for brand growth opportunities, and 3) Completely automate Stores tasks. Our vision for MLOE is to achieve ML operational excellence across Amazon through continuous innovation, scalable infrastructure, and a data-driven approach to optimize value, efficiency, and reliability. We focus on key areas for enhancing machine learning operations: a) Model Evaluation: Expanding LLM-based audit platform to support multilingual and multimodal auditing. Developing an LLM-powered testing framework for conversational systems to automate the validation of conversational flows, ensuring scalable, accurate, and efficient end-to-end testing. b) Guardrails: Building common guardrail APIs that teams can integrate to detect and prevent egregious errors, knowledge grounding issues, PII breaches, and biases. c) Deployment Framework support LLM deployments and seamlessly integrate it with our release management processes. BASIC QUALIFICATIONS • Bachelor's degree in Quantitative or STEM disciplines (Science, Technology, Engineering, Mathematics) • 3+ years of relevant work experience in solving real world business problems using machine learning, deep learning, data mining and statistical algorithms • Strong hands-on programming skills in Python, SQL, Hadoop/Hive. Additional knowledge of Spark, Scala, R, Java desired but not mandatory • Strong analytical thinking • Ability to creatively solve business problems, innovating new approaches where required and articulating ideas to a wide range of audiences using strong data, written and verbal communication skills - -• Ability to collaborate effectively across multiple teams and stakeholders, including development teams, product management and operations. PREFERRED QUALIFICATIONS • Master's degree with specialization in ML, NLP or Computer Vision preferred • 3+ years relevant work experience in a related field/s (project management, customer advocate, product owner, engineering, business analysis) • Diverse experience will be favored eg. a mix of experience across different roles - In-depth understanding of machine learning concepts including developing models and tuning the hyper-parameters, as well as deploying models and building ML service - Technical expertise, experience in Data science, ML and Statistics Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. Posted: June 11, 2025 (Updated 43 minutes ago) Posted: June 10, 2025 (Updated about 6 hours ago) Posted: June 10, 2025 (Updated about 6 hours ago) Posted: June 10, 2025 (Updated about 8 hours ago) Posted: June 10, 2025 (Updated about 8 hours ago) Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Jun 27, 2025
Full time
Business Research Analyst - II, RBS Tech As a Research Analyst, you'll collaborate with experts to develop cutting-edge ML and Gen AI/LLM solutions for business needs. You'll drive product pilots, demonstrating innovative thinking and customer focus. You'll build scalable solutions, write high-quality code, and develop state-of-the-art ML models. You'll coordinate between science and software teams, optimizing solutions. The role requires thriving in ambiguous, fast-paced environments and working independently with ML models. Key job responsibilities • Collaborate with seasoned Applied Scientists and propose best in class ML solutions for business requirements • Dive deep to drive product pilots, demonstrate think big and customer obsession LPs to steer the product roadmap • Build scalable solutions in partnership with Applied Scientists by developing technical intuition to write high quality code and develop state of the art ML models utilizing most recent research breakthroughs in academia and industry • Coordinate design efforts between Sciences and Software teams to deliver optimized solutions • Ability to thrive in an ambiguous, uncertain and fast moving ML usecase developments. • Familiar with ML models and work independent. • Mentor Junior Research Analyst (RAs) and contribute to RA hiring About the team Retail Business Services Technology (RBS Tech) team develops the systems and science to accelerate Amazon's flywheel. The team drives three core themes: 1) Find and Fix all customer and selling partner experience (CX and SPX) defects using technology, 2) Generate comprehensive insights for brand growth opportunities, and 3) Completely automate Stores tasks. Our vision for MLOE is to achieve ML operational excellence across Amazon through continuous innovation, scalable infrastructure, and a data-driven approach to optimize value, efficiency, and reliability. We focus on key areas for enhancing machine learning operations: a) Model Evaluation: Expanding LLM-based audit platform to support multilingual and multimodal auditing. Developing an LLM-powered testing framework for conversational systems to automate the validation of conversational flows, ensuring scalable, accurate, and efficient end-to-end testing. b) Guardrails: Building common guardrail APIs that teams can integrate to detect and prevent egregious errors, knowledge grounding issues, PII breaches, and biases. c) Deployment Framework support LLM deployments and seamlessly integrate it with our release management processes. BASIC QUALIFICATIONS • Bachelor's degree in Quantitative or STEM disciplines (Science, Technology, Engineering, Mathematics) • 3+ years of relevant work experience in solving real world business problems using machine learning, deep learning, data mining and statistical algorithms • Strong hands-on programming skills in Python, SQL, Hadoop/Hive. Additional knowledge of Spark, Scala, R, Java desired but not mandatory • Strong analytical thinking • Ability to creatively solve business problems, innovating new approaches where required and articulating ideas to a wide range of audiences using strong data, written and verbal communication skills - -• Ability to collaborate effectively across multiple teams and stakeholders, including development teams, product management and operations. PREFERRED QUALIFICATIONS • Master's degree with specialization in ML, NLP or Computer Vision preferred • 3+ years relevant work experience in a related field/s (project management, customer advocate, product owner, engineering, business analysis) • Diverse experience will be favored eg. a mix of experience across different roles - In-depth understanding of machine learning concepts including developing models and tuning the hyper-parameters, as well as deploying models and building ML service - Technical expertise, experience in Data science, ML and Statistics Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. Posted: June 11, 2025 (Updated 43 minutes ago) Posted: June 10, 2025 (Updated about 6 hours ago) Posted: June 10, 2025 (Updated about 6 hours ago) Posted: June 10, 2025 (Updated about 8 hours ago) Posted: June 10, 2025 (Updated about 8 hours ago) Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Startups Applied Scientist, Generative AI Innovation & Delivery Team Do you have deep technical GenAI background in the Startup space? Are you looking to work with world leading startups at the forefront of Generative AI? Join the The Generative AI Innovation and Delivery Team (GenAIID) Startup Organization! The Generative AI Innovation and Delivery mission is to drive startup innovation by making AWS the preferred GenAI Platform for startups to experiment, build and scale their products. We are a team of strategists, scientists, engineers, and architects working closely with worlds' leading startups across GenAI model providers, GenAI tooling and applications. We partner closely with startups to address their GenAI infrastructure needs, evolve their GenAI product and infuse GenAI into their existing SaaS applications. In this process we provide guidance on best practices for applying generative AI responsibly and cost efficiently. You will work directly with startups and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. We're looking for Applied Scientists passionate about helping startups use GenAI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. Key job responsibilities Collaborate with AI/ML scientists and engineers to research, design, develop, and evaluate generative AI solutions to address real-world opportunities Interact with customers directly to understand their business problems, aid them in implementation of generative AI solutions, brief customers and guide them on adoption patterns and paths to production Help customers optimize their solutions through approaches such as model selection, training or tuning, right-sizing, distillation, and hardware optimization Develop a deep understanding of startups GenAI ecosystem and their evolving technical needs to drive improvements to startups program and resulting customer experience Provide customer and market feedback to product and engineering teams to help define product direction Unlock scale by identifying patterns and establishing reusable assets to accelerate customer impact of future engagements About the team AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud. Minimum Qualifications - PhD, or Master's degree and 6+ years of applied research experience - 5+ years of hands on experience with Python to build, train, and evaluate models - Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing - Experience with design, development, and optimization of generative AI solutions, algorithms, or technologies - Experience in patents or publications at peer-reviewed conferences or journals - Experience working in a startup or with startup customers - Experience with design, deployment, and evaluation of Large Language Model (LLM)-powered agents and tools and orchestration approaches - Hands-on experience with model customization techniques such as fine-tuning, continued pre-training, and LLM-as-judge evaluation - Experience with optimization of models on GPUs, Amazon Silicon, or TPUs, also experience with open source frameworks for building applications powered by LLMs like LangChain, LlamaIndex, and/ or similar tools - Experience building generative AI applications on AWS using services such as Amazon Bedrock and Amazon SageMaker Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( ) to know more about how we collect, use and transfer the personal data of our candidates. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.
Jun 07, 2025
Full time
Startups Applied Scientist, Generative AI Innovation & Delivery Team Do you have deep technical GenAI background in the Startup space? Are you looking to work with world leading startups at the forefront of Generative AI? Join the The Generative AI Innovation and Delivery Team (GenAIID) Startup Organization! The Generative AI Innovation and Delivery mission is to drive startup innovation by making AWS the preferred GenAI Platform for startups to experiment, build and scale their products. We are a team of strategists, scientists, engineers, and architects working closely with worlds' leading startups across GenAI model providers, GenAI tooling and applications. We partner closely with startups to address their GenAI infrastructure needs, evolve their GenAI product and infuse GenAI into their existing SaaS applications. In this process we provide guidance on best practices for applying generative AI responsibly and cost efficiently. You will work directly with startups and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. We're looking for Applied Scientists passionate about helping startups use GenAI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. Key job responsibilities Collaborate with AI/ML scientists and engineers to research, design, develop, and evaluate generative AI solutions to address real-world opportunities Interact with customers directly to understand their business problems, aid them in implementation of generative AI solutions, brief customers and guide them on adoption patterns and paths to production Help customers optimize their solutions through approaches such as model selection, training or tuning, right-sizing, distillation, and hardware optimization Develop a deep understanding of startups GenAI ecosystem and their evolving technical needs to drive improvements to startups program and resulting customer experience Provide customer and market feedback to product and engineering teams to help define product direction Unlock scale by identifying patterns and establishing reusable assets to accelerate customer impact of future engagements About the team AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud. Minimum Qualifications - PhD, or Master's degree and 6+ years of applied research experience - 5+ years of hands on experience with Python to build, train, and evaluate models - Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing - Experience with design, development, and optimization of generative AI solutions, algorithms, or technologies - Experience in patents or publications at peer-reviewed conferences or journals - Experience working in a startup or with startup customers - Experience with design, deployment, and evaluation of Large Language Model (LLM)-powered agents and tools and orchestration approaches - Hands-on experience with model customization techniques such as fine-tuning, continued pre-training, and LLM-as-judge evaluation - Experience with optimization of models on GPUs, Amazon Silicon, or TPUs, also experience with open source frameworks for building applications powered by LLMs like LangChain, LlamaIndex, and/ or similar tools - Experience building generative AI applications on AWS using services such as Amazon Bedrock and Amazon SageMaker Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( ) to know more about how we collect, use and transfer the personal data of our candidates. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.
Startups Sr. Applied Scientist, Generative AI Innovation & Delivery Team Job ID: AWS EMEA SARL (UK Branch) Do you have deep technical GenAI background in the Startup space? Are you looking to work with world leading startups at the forefront of Generative AI? Join the The Generative AI Innovation and Delivery Team (GenAIID) Startup Organization! The Generative AI Innovation and Delivery mission is to drive startup innovation by making AWS the preferred GenAI Platform for startups to experiment, build and scale their products. We are a team of strategists, scientists, engineers, and architects working closely with worlds' leading startups across GenAI model providers, GenAI tooling and applications. We partner closely with startups to address their GenAI infrastructure needs, evolve their GenAI product and infuse GenAI into their existing SaaS applications. In this process we provide guidance on best practices for applying generative AI responsibly and cost efficiently. You will work directly with startups and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. We're looking for Applied Scientists passionate about helping startups use GenAI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. Key job responsibilities Collaborate with AI/ML scientists and engineers to research, design, develop, and evaluate generative AI solutions to address real-world opportunities Interact with customers directly to understand their business problems, aid them in implementation of generative AI solutions, brief customers and guide them on adoption patterns and paths to production Help customers optimize their solutions through approaches such as model selection, training or tuning, right-sizing, distillation, and hardware optimization Develop a deep understanding of startups GenAI ecosystem and their evolving technical needs to drive improvements to startups program and resulting customer experience Provide customer and market feedback to product and engineering teams to help define product direction Unlock scale by identifying patterns and establishing reusable assets to accelerate customer impact of future engagements About the team AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud. BASIC QUALIFICATIONS - PhD, or Master's degree and 6+ years of applied research experience - 5+ years of hands on experience with Python to build, train, and evaluate models - 5+ years of experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing - 2+ years of experience with design, development, and optimization of generative AI solutions, algorithms, or technologies - Experience in patents or publications at peer-reviewed conferences or journals PREFERRED QUALIFICATIONS - Experience working in a startup or with startup customers - Experience with design, deployment, and evaluation of Large Language Model (LLM)-powered agents and tools and orchestration approaches - Hands-on experience with model customization techniques such as fine-tuning, continued pre-training, and LLM-as-judge evaluation - Experience with optimization of models on GPUs, Amazon Silicon, or TPUs, also experience with open source frameworks for building applications powered by LLMs like LangChain, LlamaIndex, and/ or similar tools - Experience building generative AI applications on AWS using services such as Amazon Bedrock and Amazon SageMaker Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( ) to know more about how we collect, use and transfer the personal data of our candidates. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. Posted: April 2, 2025 (Updated 1 day ago) Posted: March 3, 2025 (Updated 4 days ago) Posted: April 3, 2024 (Updated 6 days ago) Posted: April 28, 2025 (Updated 8 days ago) Posted: April 22, 2025 (Updated 14 days ago) Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Jun 06, 2025
Full time
Startups Sr. Applied Scientist, Generative AI Innovation & Delivery Team Job ID: AWS EMEA SARL (UK Branch) Do you have deep technical GenAI background in the Startup space? Are you looking to work with world leading startups at the forefront of Generative AI? Join the The Generative AI Innovation and Delivery Team (GenAIID) Startup Organization! The Generative AI Innovation and Delivery mission is to drive startup innovation by making AWS the preferred GenAI Platform for startups to experiment, build and scale their products. We are a team of strategists, scientists, engineers, and architects working closely with worlds' leading startups across GenAI model providers, GenAI tooling and applications. We partner closely with startups to address their GenAI infrastructure needs, evolve their GenAI product and infuse GenAI into their existing SaaS applications. In this process we provide guidance on best practices for applying generative AI responsibly and cost efficiently. You will work directly with startups and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. We're looking for Applied Scientists passionate about helping startups use GenAI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. Key job responsibilities Collaborate with AI/ML scientists and engineers to research, design, develop, and evaluate generative AI solutions to address real-world opportunities Interact with customers directly to understand their business problems, aid them in implementation of generative AI solutions, brief customers and guide them on adoption patterns and paths to production Help customers optimize their solutions through approaches such as model selection, training or tuning, right-sizing, distillation, and hardware optimization Develop a deep understanding of startups GenAI ecosystem and their evolving technical needs to drive improvements to startups program and resulting customer experience Provide customer and market feedback to product and engineering teams to help define product direction Unlock scale by identifying patterns and establishing reusable assets to accelerate customer impact of future engagements About the team AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud. BASIC QUALIFICATIONS - PhD, or Master's degree and 6+ years of applied research experience - 5+ years of hands on experience with Python to build, train, and evaluate models - 5+ years of experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing - 2+ years of experience with design, development, and optimization of generative AI solutions, algorithms, or technologies - Experience in patents or publications at peer-reviewed conferences or journals PREFERRED QUALIFICATIONS - Experience working in a startup or with startup customers - Experience with design, deployment, and evaluation of Large Language Model (LLM)-powered agents and tools and orchestration approaches - Hands-on experience with model customization techniques such as fine-tuning, continued pre-training, and LLM-as-judge evaluation - Experience with optimization of models on GPUs, Amazon Silicon, or TPUs, also experience with open source frameworks for building applications powered by LLMs like LangChain, LlamaIndex, and/ or similar tools - Experience building generative AI applications on AWS using services such as Amazon Bedrock and Amazon SageMaker Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( ) to know more about how we collect, use and transfer the personal data of our candidates. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. Posted: April 2, 2025 (Updated 1 day ago) Posted: March 3, 2025 (Updated 4 days ago) Posted: April 3, 2024 (Updated 6 days ago) Posted: April 28, 2025 (Updated 8 days ago) Posted: April 22, 2025 (Updated 14 days ago) Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Expedia Group brands power global travel for everyone, everywhere. We design cutting-edge tech to make travel smoother and more memorable, and we create groundbreaking solutions for our partners. Our diverse, vibrant, and welcoming community is essential in driving our success. Why Join Us? To shape the future of travel, people must come first. Guided by our Values and Leadership Agreements, we foster an open culture where everyone belongs, differences are celebrated and know that when one of us wins, we all win. We provide a full benefits package, including exciting travel perks, generous time-off, parental leave, a global hybrid work setup (with some pretty cool offices), and career development resources, all to fuel our employees' passion for travel and ensure a rewarding career journey. We re building a more open world. Join us. The Traveler Business Team builds and drives growth for our global consumer businesses-Expedia, and Vrbo. This division creates compelling and differentiated traveler value for each brand by setting the strategic vision, operating strategy, and plan. Responsibilities include investment allocation and prioritization, P&L accountability, and leading cross-functional teams across Expedia Group, who are all held accountable to a single scorecard. The Supply Marketing team is a marketing powerhouse known for effective strategies and exceptional talent. We use insights to create impactful stories and influence partner behavior, driving measurable success and a deeper connection to Expedia Group. Through collaboration and valuable propositions, we drive the growth of both our partners and Expedia Group. Growing Supply depth and quality is core to Expedia Group's strategy - we want travellers to trust they ll find the perfect fit at a competitive rate. As a member of the Hotel & Sales Analytics team, you will leverage data and analytics to help drive decision related to both acquisition of new partners and engagement of existing partners. You will ultimately impact millions of travellers around the world. We are looking for a passionate and experienced Data Scientist to provide valuable insights and decision-making support to Expedia s Supply Marketing leadership while partnering with Analytics, Engineering, Brands and Strategy & Transformation colleagues. In this role, you will: Collaborate closely with stakeholders to define relevant KPIs and initiatives driving supply growth; translate business needs into analytical solutions, and align on project priorities. Build comprehensive marketing data ecosystem in collaboration with data engineering teams; build robust and actionable self-service capabilities to be used by stakeholders, peers and Expedia Group Leadership; build advanced analytics solutions and models to help define and measure causality. Advise stakeholders through clear communication and relevant insights, acting as data-driven advisor to business. Display a proactive mindset, strive for continuous process and structural improvement, and use critical thinking to propose innovative solutions. Experience and qualifications: 4+ years of experience in a data focused company environment (analytics, data science, consulting, etc.) and have an academic background in a quantitative or business discipline. 3+ years SQL and Python (or similar) coding experience, incl. applied experience on advanced statistical/predictive modelling projects; Marketing analytics projects a plus (MMM, MTA, Channel Incrementality, Segmentation, ). 2+ years experience with data visualization tool; Tableau a plus. Knowledge on Marketing pixels and conversion APIs a plus; Knowledge on Digital Analytics/Web analytics a plus. Excellent Business acumen, problem-solving, intellectual curiosity and self-motivation skills. You strive in collaborative environment, have a passion for driving business impact and execution, and are a team player. Accommodation requests If you need assistance with any part of the application or recruiting process due to a disability, or other physical or mental health conditions, please reach out to our Recruiting Accommodations Team through the Accommodation Request. We are proud to be named as a Best Place to Work on Glassdoor in 2024 and be recognized for award-winning culture by organizations like Forbes, TIME, Disability:IN, and others. Expedia Group's family of brands includes: Brand Expediareg; Expediareg; Partner Solutions, Vrboreg;, trivagoreg;, Orbitzreg;, Travelocityreg;, Hotwirereg;, Wotifreg;, ebookersreg;, CheapTicketsreg;, Expedia Group Media Solutions, Expedia Local Expertreg;, and Expedia Cruises. 2024 Expedia, Inc. All rights reserved. Trademarks and logos are the property of their respective owners. CST: -50. Employment opportunities and job offers at Expedia Group will always come from Expedia Group s Talent Acquisition and hiring teams. Never provide sensitive, personal information to someone unless you re confident who the recipient is. Expedia Group does not extend job offers via email or any other messaging tools to individuals with whom we have not made prior contact. Our email domain The official website to find and apply for job openings at Expedia Group is Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, gender, sexual orientation, national origin, disability or age.
Feb 21, 2025
Full time
Expedia Group brands power global travel for everyone, everywhere. We design cutting-edge tech to make travel smoother and more memorable, and we create groundbreaking solutions for our partners. Our diverse, vibrant, and welcoming community is essential in driving our success. Why Join Us? To shape the future of travel, people must come first. Guided by our Values and Leadership Agreements, we foster an open culture where everyone belongs, differences are celebrated and know that when one of us wins, we all win. We provide a full benefits package, including exciting travel perks, generous time-off, parental leave, a global hybrid work setup (with some pretty cool offices), and career development resources, all to fuel our employees' passion for travel and ensure a rewarding career journey. We re building a more open world. Join us. The Traveler Business Team builds and drives growth for our global consumer businesses-Expedia, and Vrbo. This division creates compelling and differentiated traveler value for each brand by setting the strategic vision, operating strategy, and plan. Responsibilities include investment allocation and prioritization, P&L accountability, and leading cross-functional teams across Expedia Group, who are all held accountable to a single scorecard. The Supply Marketing team is a marketing powerhouse known for effective strategies and exceptional talent. We use insights to create impactful stories and influence partner behavior, driving measurable success and a deeper connection to Expedia Group. Through collaboration and valuable propositions, we drive the growth of both our partners and Expedia Group. Growing Supply depth and quality is core to Expedia Group's strategy - we want travellers to trust they ll find the perfect fit at a competitive rate. As a member of the Hotel & Sales Analytics team, you will leverage data and analytics to help drive decision related to both acquisition of new partners and engagement of existing partners. You will ultimately impact millions of travellers around the world. We are looking for a passionate and experienced Data Scientist to provide valuable insights and decision-making support to Expedia s Supply Marketing leadership while partnering with Analytics, Engineering, Brands and Strategy & Transformation colleagues. In this role, you will: Collaborate closely with stakeholders to define relevant KPIs and initiatives driving supply growth; translate business needs into analytical solutions, and align on project priorities. Build comprehensive marketing data ecosystem in collaboration with data engineering teams; build robust and actionable self-service capabilities to be used by stakeholders, peers and Expedia Group Leadership; build advanced analytics solutions and models to help define and measure causality. Advise stakeholders through clear communication and relevant insights, acting as data-driven advisor to business. Display a proactive mindset, strive for continuous process and structural improvement, and use critical thinking to propose innovative solutions. Experience and qualifications: 4+ years of experience in a data focused company environment (analytics, data science, consulting, etc.) and have an academic background in a quantitative or business discipline. 3+ years SQL and Python (or similar) coding experience, incl. applied experience on advanced statistical/predictive modelling projects; Marketing analytics projects a plus (MMM, MTA, Channel Incrementality, Segmentation, ). 2+ years experience with data visualization tool; Tableau a plus. Knowledge on Marketing pixels and conversion APIs a plus; Knowledge on Digital Analytics/Web analytics a plus. Excellent Business acumen, problem-solving, intellectual curiosity and self-motivation skills. You strive in collaborative environment, have a passion for driving business impact and execution, and are a team player. Accommodation requests If you need assistance with any part of the application or recruiting process due to a disability, or other physical or mental health conditions, please reach out to our Recruiting Accommodations Team through the Accommodation Request. We are proud to be named as a Best Place to Work on Glassdoor in 2024 and be recognized for award-winning culture by organizations like Forbes, TIME, Disability:IN, and others. Expedia Group's family of brands includes: Brand Expediareg; Expediareg; Partner Solutions, Vrboreg;, trivagoreg;, Orbitzreg;, Travelocityreg;, Hotwirereg;, Wotifreg;, ebookersreg;, CheapTicketsreg;, Expedia Group Media Solutions, Expedia Local Expertreg;, and Expedia Cruises. 2024 Expedia, Inc. All rights reserved. Trademarks and logos are the property of their respective owners. CST: -50. Employment opportunities and job offers at Expedia Group will always come from Expedia Group s Talent Acquisition and hiring teams. Never provide sensitive, personal information to someone unless you re confident who the recipient is. Expedia Group does not extend job offers via email or any other messaging tools to individuals with whom we have not made prior contact. Our email domain The official website to find and apply for job openings at Expedia Group is Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, gender, sexual orientation, national origin, disability or age.
