Overview About Aqemia Aqemia is a next-generation pharmatech reinventing drug discovery with quantum-inspired physics and generative AI. Our mission: design innovative small-molecule drug candidates for dozens of critical diseases, faster and smarter, without relying on experimental data. Unlike traditional approaches, Aqemia starts drug discovery purely in silico. By combining physics-based models with large language models trained on proprietary data, we identify promising molecules with high accuracy before synthesis. We've already delivered multiple preclinical successes and secured strategic partnership. Our internal pipeline is growing fast, with several programs in in vivo optimization. We're a team of 65+ based in Paris and London, we bring together chemists, physicists, engineers, and machine learning experts to push the boundaries of what's possible in early-stage drug discovery. The Role As a Senior ML Software Engineer in the DH Team, you will focus on building and scaling the platform-facing product that manages the full lifecycle of Aqemia's predictive models, our core scientific assets. You'll scale and industrialize ML/deep learning models developed by research scientists, so they can be efficiently served to our Drug Hunter community. You will play a critical role in the development, deployment, and maintenance of single predictors, ensuring they are robust, reproducible, and seamlessly integrated into the platform that drives our drug discovery engine. This role is deeply technical and foundational to our platform's performance, reliability, and scalability. What you'll do Design and implement ML product and infrastructure to support the training, evaluation, deployment, and versioning of predictive models Industrialize and optimize ML/deep learning models developed by scientists, making them scalable and cost-efficient in production Collaborate closely with scientists to integrate diverse predictors (physics-based, AI-based, hybrid) into the platform Ensure reproducibility, traceability, and performance of model pipelines across the full lifecycle Develop APIs and tools that expose predictors as scalable services to other teams Contribute to software engineering best practices across the ML stack (testing, CI/CD, observability) Partner with platform engineers and product stakeholders to ensure technical alignment and delivery What we're looking for 6+ years of experience in software engineering with strong focus on machine learning systems Deep proficiency in Python and ML ecosystem (e.g. PyTorch, scikit-learn, MLFlow) Solid understanding of data and model lifecycle management, versioning, and deployment Experience building ML infrastructure and model-serving pipelines in production environments Familiarity with cloud-based architecture (AWS preferred), containerization (Docker), and orchestration tools Ability to work autonomously and lead initiatives with high technical ownership Strong communication skills and ability to work closely with scientists and engineers alike Preferred mindset You care about building solid foundations for ML at scale You combine scientific curiosity with software engineering rigor You enjoy tackling complexity and finding elegant, maintainable solutions You thrive in a cross-functional, fast-moving environment where models meet production Why Join Us At Aqemia, engineers don't just build software, they help discover real drugs . You'll work at the intersection of AI, physics and chemistry, transforming bold scientific ideas into robust, production-grade tools that accelerate discovery. DeepTech Mission : Build the platform that powers AI-driven drug discovery, combining quantum-inspired physics with generative models Real-World Impact : Every feature shipped helps scientists prioritize molecules and design better candidates, faster Modern Stack & Challenges : Python, FastAPI, Airflow, Snowflake, Kubernetes, ML workflows, scientific infra, data engineering at scale High Ownership, High Impact : Engineers contribute to architecture, tooling, and scientific decision-making Interdisciplinary Team : Collaborate with chemists, physicists, ML researchers, and product teams Prime Locations : Central Paris or London offices, with 2 remote days/week Strategic Traction : Backed by $100M in funding and a $140M partnership with Sanofi Join us if you're excited to shape the future of AI-driven drug discovery, and want your code to change the course of real diseases.
Jan 01, 2026
Full time
Overview About Aqemia Aqemia is a next-generation pharmatech reinventing drug discovery with quantum-inspired physics and generative AI. Our mission: design innovative small-molecule drug candidates for dozens of critical diseases, faster and smarter, without relying on experimental data. Unlike traditional approaches, Aqemia starts drug discovery purely in silico. By combining physics-based models with large language models trained on proprietary data, we identify promising molecules with high accuracy before synthesis. We've already delivered multiple preclinical successes and secured strategic partnership. Our internal pipeline is growing fast, with several programs in in vivo optimization. We're a team of 65+ based in Paris and London, we bring together chemists, physicists, engineers, and machine learning experts to push the boundaries of what's possible in early-stage drug discovery. The Role As a Senior ML Software Engineer in the DH Team, you will focus on building and scaling the platform-facing product that manages the full lifecycle of Aqemia's predictive models, our core scientific assets. You'll scale and industrialize ML/deep learning models developed by research scientists, so they can be efficiently served to our Drug Hunter community. You will play a critical role in the development, deployment, and maintenance of single predictors, ensuring they are robust, reproducible, and seamlessly integrated into the platform that drives our drug discovery engine. This role is deeply technical and foundational to our platform's performance, reliability, and scalability. What you'll do Design and implement ML product and infrastructure to support the training, evaluation, deployment, and versioning of predictive models Industrialize and optimize ML/deep learning models developed by scientists, making them scalable and cost-efficient in production Collaborate closely with scientists to integrate diverse predictors (physics-based, AI-based, hybrid) into the platform Ensure reproducibility, traceability, and performance of model pipelines across the full lifecycle Develop APIs and tools that expose predictors as scalable services to other teams Contribute to software engineering best practices across the ML stack (testing, CI/CD, observability) Partner with platform engineers and product stakeholders to ensure technical alignment and delivery What we're looking for 6+ years of experience in software engineering with strong focus on machine learning systems Deep proficiency in Python and ML ecosystem (e.g. PyTorch, scikit-learn, MLFlow) Solid understanding of data and model lifecycle management, versioning, and deployment Experience building ML infrastructure and model-serving pipelines in production environments Familiarity with cloud-based architecture (AWS preferred), containerization (Docker), and orchestration tools Ability to work autonomously and lead initiatives with high technical ownership Strong communication skills and ability to work closely with scientists and engineers alike Preferred mindset You care about building solid foundations for ML at scale You combine scientific curiosity with software engineering rigor You enjoy tackling complexity and finding elegant, maintainable solutions You thrive in a cross-functional, fast-moving environment where models meet production Why Join Us At Aqemia, engineers don't just build software, they help discover real drugs . You'll work at the intersection of AI, physics and chemistry, transforming bold scientific ideas into robust, production-grade tools that accelerate discovery. DeepTech Mission : Build the platform that powers AI-driven drug discovery, combining quantum-inspired physics with generative models Real-World Impact : Every feature shipped helps scientists prioritize molecules and design better candidates, faster Modern Stack & Challenges : Python, FastAPI, Airflow, Snowflake, Kubernetes, ML workflows, scientific infra, data engineering at scale High Ownership, High Impact : Engineers contribute to architecture, tooling, and scientific decision-making Interdisciplinary Team : Collaborate with chemists, physicists, ML researchers, and product teams Prime Locations : Central Paris or London offices, with 2 remote days/week Strategic Traction : Backed by $100M in funding and a $140M partnership with Sanofi Join us if you're excited to shape the future of AI-driven drug discovery, and want your code to change the course of real diseases.
About Aqemia Aqemia is a next-generation pharmatech reinventing drug discovery with quantum-inspired physics and generative AI. Our mission: design innovative small-molecule drug candidates for dozens of critical diseases, faster and smarter, without relying on experimental data. Unlike traditional approaches, Aqemia starts drug discovery purely in silico. By combining physics-based models with large language models trained on proprietary data, we identify promising molecules with high accuracy before synthesis. We've already delivered multiple preclinical successes and secured strategic partnership. Our internal pipeline is growing fast, with several programs in in vivo optimization. We're a team of 65+ based in Paris and London, we bring together chemists, physicists, engineers, and machine learning experts to push the boundaries of what's possible in early-stage drug discovery. The Role As a Scientific Software Engineer in the product team supporting the daily activities of scientists (physics, ML, deep learning) producing predictors and prediction workflows,you'll contribute to scaling the scientific logic and software that connect Aqemia's predictive models into advanced drug discovery workflows. You'll build the engine that enables large-scale computation and seamless data transformation. You'll work at the interface of cheminformatics, software engineering, and platform infrastructure, translating scientific needs into robust, scalable tools used daily across Aqemia's pipeline. What you'll do Build, scale, and maintain cheminformatics predictors and workflows that power multi-step prediction pipelines Translate scientific strategies into software components that operate at scale Collaborate with ML engineers and platform teams to integrate chemical logic into orchestrated flows Work with internal chemical libraries, molecular formats, and property calculations Build, scale, and maintain cheminformatics predictors and workflows that power multi-step prediction pipelines Ensure robustness, performance, cost effectiveness, and traceability of cheminformatics tools Stay up to date with advances in cheminformatics and contribute to continuous improvement What we're looking for 2 - 4 years of experience in cheminformatics or computational chemistry, ideally in a drug discovery context Strong Python skills and experience with RDKit or similar libraries Familiarity with compound library design, molecular descriptors, and property prediction Ability to work with data scientists, ML engineers, and software teams Strong sense of code quality, testing, and documentation Good communication skills and collaborative mindset Experience in scaling complex scientific logic and reducing computational workload when industrializing research-grade code Preferred mindset You're excited to bring chemistry into the heart of automated scientific workflows You enjoy transforming abstract scientific logic into robust, maintainable, production-grade software You thrive in interdisciplinary environments You're driven to build tools that make a tangible impact on drug discovery You care about scalability, not just in infrastructure, but also in complexity, efficiency, and scientific throughput Why Join Us At Aqemia, engineers don't just build software, they help discover real drugs.You 'll work at the intersection of AI, physics and chemistry, transforming bold scientific ideas into robust, production-grade tools that accelerate discovery. DeepTech Mission : Build the platform that powers AI-driven drug discovery, combining quantum-inspired physics with generative models Real-World Impact : Every feature shipped helps scientists prioritize molecules and design better candidates, faster Modern Stack & Challenges : Python, FastAPI, Airflow, Snowflake, Kubernetes, ML workflows, scientific infra, data engineering at scale High Ownership, High Impact : Engineers contribute to architecture, tooling, and scientific decision-making Interdisciplinary Team : Collaborate with chemists, physicists, ML researchers, and product teams Prime Locations : Central Paris or London offices, with 2 remote days/week Strategic Traction : Backed by $100M in funding and a $140M partnership with Sanofi Join us if you're excited to shape the future of AI-driven drug discovery, and want your code to change the course of real diseases.
Jan 01, 2026
Full time
About Aqemia Aqemia is a next-generation pharmatech reinventing drug discovery with quantum-inspired physics and generative AI. Our mission: design innovative small-molecule drug candidates for dozens of critical diseases, faster and smarter, without relying on experimental data. Unlike traditional approaches, Aqemia starts drug discovery purely in silico. By combining physics-based models with large language models trained on proprietary data, we identify promising molecules with high accuracy before synthesis. We've already delivered multiple preclinical successes and secured strategic partnership. Our internal pipeline is growing fast, with several programs in in vivo optimization. We're a team of 65+ based in Paris and London, we bring together chemists, physicists, engineers, and machine learning experts to push the boundaries of what's possible in early-stage drug discovery. The Role As a Scientific Software Engineer in the product team supporting the daily activities of scientists (physics, ML, deep learning) producing predictors and prediction workflows,you'll contribute to scaling the scientific logic and software that connect Aqemia's predictive models into advanced drug discovery workflows. You'll build the engine that enables large-scale computation and seamless data transformation. You'll work at the interface of cheminformatics, software engineering, and platform infrastructure, translating scientific needs into robust, scalable tools used daily across Aqemia's pipeline. What you'll do Build, scale, and maintain cheminformatics predictors and workflows that power multi-step prediction pipelines Translate scientific strategies into software components that operate at scale Collaborate with ML engineers and platform teams to integrate chemical logic into orchestrated flows Work with internal chemical libraries, molecular formats, and property calculations Build, scale, and maintain cheminformatics predictors and workflows that power multi-step prediction pipelines Ensure robustness, performance, cost effectiveness, and traceability of cheminformatics tools Stay up to date with advances in cheminformatics and contribute to continuous improvement What we're looking for 2 - 4 years of experience in cheminformatics or computational chemistry, ideally in a drug discovery context Strong Python skills and experience with RDKit or similar libraries Familiarity with compound library design, molecular descriptors, and property prediction Ability to work with data scientists, ML engineers, and software teams Strong sense of code quality, testing, and documentation Good communication skills and collaborative mindset Experience in scaling complex scientific logic and reducing computational workload when industrializing research-grade code Preferred mindset You're excited to bring chemistry into the heart of automated scientific workflows You enjoy transforming abstract scientific logic into robust, maintainable, production-grade software You thrive in interdisciplinary environments You're driven to build tools that make a tangible impact on drug discovery You care about scalability, not just in infrastructure, but also in complexity, efficiency, and scientific throughput Why Join Us At Aqemia, engineers don't just build software, they help discover real drugs.You 'll work at the intersection of AI, physics and chemistry, transforming bold scientific ideas into robust, production-grade tools that accelerate discovery. DeepTech Mission : Build the platform that powers AI-driven drug discovery, combining quantum-inspired physics with generative models Real-World Impact : Every feature shipped helps scientists prioritize molecules and design better candidates, faster Modern Stack & Challenges : Python, FastAPI, Airflow, Snowflake, Kubernetes, ML workflows, scientific infra, data engineering at scale High Ownership, High Impact : Engineers contribute to architecture, tooling, and scientific decision-making Interdisciplinary Team : Collaborate with chemists, physicists, ML researchers, and product teams Prime Locations : Central Paris or London offices, with 2 remote days/week Strategic Traction : Backed by $100M in funding and a $140M partnership with Sanofi Join us if you're excited to shape the future of AI-driven drug discovery, and want your code to change the course of real diseases.
About Aqemia Aqemia is a next-generation pharmatech reinventing drug discovery with quantum-inspired physics and generative AI. Our mission: design innovative small-molecule drug candidates for dozens of critical diseases, faster and smarter, without relying on experimental data. Unlike traditional approaches, Aqemia starts drug discovery purely in silico. By combining physics-based models with large language models trained on proprietary data, we identify promising molecules with high accuracy before synthesis. We've already delivered multiple preclinical successes and secured strategic partnership. Our internal pipeline is growing fast, with several programs in in vivo optimization. We're a team of 65+ based in Paris and London, we bring together chemists, physicists, engineers, and machine learning experts to push the boundaries of what's possible in early-stage drug discovery. About the team you'll join As Principal Computational Chemist, you'll lead the development of cutting-edge computational chemistry pipelines within Aq's Drug Discovery Platform. Collaborating with computational chemists, AI researchers, and drug discovery experts, you'll integrate innovations to accelerate novel therapeutic discovery. About the Role We are seeking a Principal Computational Chemist, the most senior individual contributor rank at Aqemia. This role is designed for a scientist at the state of the art of their field, with deep expertise and a strong track record of impactful contributions. The Principal Computational Chemist will oversee complex scientific projects, mentor scientists, and actively shape our scientific roadmap. This means you will: Be a Technical Leader - Drive the development of cutting-edge computational chemistry methodologies for molecular modeling and drug discovery. Mentor and Support the Team - Act as a scientific and technical mentor to junior and mid-level researchers, fostering innovation and knowledge-sharing within the team. Bridge Research and Application - Work closely with interdisciplinary teams (computational chemistry, AI and drug discovery experts) to translate computational chemistry research into real-world impact. Your Role Lead research initiatives to develop and apply novel computational chemistry methods to virtual screening, hit optimisation and lead optimisation. Design and implement advanced computational chemistry techniques, including protein ligand complex generation. Collaborate with interdisciplinary teams, including computational chemists, AI Research scientists, physicists, data scientists and medicinal chemists. Mentor and guide junior researchers and engineers, fostering a culture of scientific innovation and excellence. Polite note: this position does not involve manual compound design in Drug Discovery Programs. Your Profile PhD in Computational Chemistry, Biophysics, Statistical Mechanics, or a related field. Extensive experience (10+ years) in computational chemistry and drug discovery including 5 years in the drug discovery industry. Recognised expertise in molecular modeling, complex generation, protein-ligand interactions, free energy calculations, virtual screening, ADME properties and related areas. Strong knowledge of uncertainty quantification and its application in molecular design. Proven ability to deliver impactful scientific contributions at the forefront of the field. Experience mentoring and guiding scientists in a collaborative, high-performance environment. Proficiency in programming (e.g., Python) and experience with industry-standard computational chemistry tools. Strong problem-solving skills, autonomy and a collaborative mindset. Preferred Mindset Pragmatic and Impact-Driven - Focused on delivering solutions that work in real-world applications, balancing scientific rigor with practical usability. Eagerness to Learn - A strong curiosity for scientific advancements and a willingness to continuously expand your expertise. Love for High Scientific Challenges - Enthusiasm for tackling complex problems at the frontier of AI and drug discovery. Team-Oriented - A collaborative spirit, thriving in an interdisciplinary environment. Humility - Open to feedback and different perspectives, always striving for improvement. Aqemia's Recruitment team leads all recruitment activities for the company. We will not recognise any notional ownership recruitment companies claim over candidates presented directly to hiring managers without our Recruitment team's consent. Unsolicited resumes sent to us from recruiters do not constitute any type of relationship between the recruiter and Aqemia, and we will not be obligated to pay fees should we hire from those resumes. Why Join Us At Aqemia, engineers don't just build software, they help discover real drugs. You'll work at the intersection of AI, physics and chemistry, transforming bold scientific ideas into robust, production-grade tools that accelerate discovery. DeepTech Mission Build the platform that powers AI-driven drug discovery, combining quantum-inspired physics with generative models. Real-World Impact Every feature shipped helps scientists prioritize molecules and design better candidates, faster. Modern Stack & Challenges Python, FastAPI, Airflow, Snowflake, Kubernetes, ML workflows, scientific infra, data engineering at scale. High Ownership, High Impact Engineers contribute to architecture, tooling, and scientific decision-making. Interdisciplinary Team Collaborate with chemists, physicists, ML researchers, and product teams. Prime Locations Central Paris or London offices, with 2 remote days/week. Strategic Traction Backed by $100M in funding and a $140M partnership with Sanofi. Join us if you're excited to shape the future of AI-driven drug discovery, and want your code to change the course of real diseases.
Jan 01, 2026
Full time
About Aqemia Aqemia is a next-generation pharmatech reinventing drug discovery with quantum-inspired physics and generative AI. Our mission: design innovative small-molecule drug candidates for dozens of critical diseases, faster and smarter, without relying on experimental data. Unlike traditional approaches, Aqemia starts drug discovery purely in silico. By combining physics-based models with large language models trained on proprietary data, we identify promising molecules with high accuracy before synthesis. We've already delivered multiple preclinical successes and secured strategic partnership. Our internal pipeline is growing fast, with several programs in in vivo optimization. We're a team of 65+ based in Paris and London, we bring together chemists, physicists, engineers, and machine learning experts to push the boundaries of what's possible in early-stage drug discovery. About the team you'll join As Principal Computational Chemist, you'll lead the development of cutting-edge computational chemistry pipelines within Aq's Drug Discovery Platform. Collaborating with computational chemists, AI researchers, and drug discovery experts, you'll integrate innovations to accelerate novel therapeutic discovery. About the Role We are seeking a Principal Computational Chemist, the most senior individual contributor rank at Aqemia. This role is designed for a scientist at the state of the art of their field, with deep expertise and a strong track record of impactful contributions. The Principal Computational Chemist will oversee complex scientific projects, mentor scientists, and actively shape our scientific roadmap. This means you will: Be a Technical Leader - Drive the development of cutting-edge computational chemistry methodologies for molecular modeling and drug discovery. Mentor and Support the Team - Act as a scientific and technical mentor to junior and mid-level researchers, fostering innovation and knowledge-sharing within the team. Bridge Research and Application - Work closely with interdisciplinary teams (computational chemistry, AI and drug discovery experts) to translate computational chemistry research into real-world impact. Your Role Lead research initiatives to develop and apply novel computational chemistry methods to virtual screening, hit optimisation and lead optimisation. Design and implement advanced computational chemistry techniques, including protein ligand complex generation. Collaborate with interdisciplinary teams, including computational chemists, AI Research scientists, physicists, data scientists and medicinal chemists. Mentor and guide junior researchers and engineers, fostering a culture of scientific innovation and excellence. Polite note: this position does not involve manual compound design in Drug Discovery Programs. Your Profile PhD in Computational Chemistry, Biophysics, Statistical Mechanics, or a related field. Extensive experience (10+ years) in computational chemistry and drug discovery including 5 years in the drug discovery industry. Recognised expertise in molecular modeling, complex generation, protein-ligand interactions, free energy calculations, virtual screening, ADME properties and related areas. Strong knowledge of uncertainty quantification and its application in molecular design. Proven ability to deliver impactful scientific contributions at the forefront of the field. Experience mentoring and guiding scientists in a collaborative, high-performance environment. Proficiency in programming (e.g., Python) and experience with industry-standard computational chemistry tools. Strong problem-solving skills, autonomy and a collaborative mindset. Preferred Mindset Pragmatic and Impact-Driven - Focused on delivering solutions that work in real-world applications, balancing scientific rigor with practical usability. Eagerness to Learn - A strong curiosity for scientific advancements and a willingness to continuously expand your expertise. Love for High Scientific Challenges - Enthusiasm for tackling complex problems at the frontier of AI and drug discovery. Team-Oriented - A collaborative spirit, thriving in an interdisciplinary environment. Humility - Open to feedback and different perspectives, always striving for improvement. Aqemia's Recruitment team leads all recruitment activities for the company. We will not recognise any notional ownership recruitment companies claim over candidates presented directly to hiring managers without our Recruitment team's consent. Unsolicited resumes sent to us from recruiters do not constitute any type of relationship between the recruiter and Aqemia, and we will not be obligated to pay fees should we hire from those resumes. Why Join Us At Aqemia, engineers don't just build software, they help discover real drugs. You'll work at the intersection of AI, physics and chemistry, transforming bold scientific ideas into robust, production-grade tools that accelerate discovery. DeepTech Mission Build the platform that powers AI-driven drug discovery, combining quantum-inspired physics with generative models. Real-World Impact Every feature shipped helps scientists prioritize molecules and design better candidates, faster. Modern Stack & Challenges Python, FastAPI, Airflow, Snowflake, Kubernetes, ML workflows, scientific infra, data engineering at scale. High Ownership, High Impact Engineers contribute to architecture, tooling, and scientific decision-making. Interdisciplinary Team Collaborate with chemists, physicists, ML researchers, and product teams. Prime Locations Central Paris or London offices, with 2 remote days/week. Strategic Traction Backed by $100M in funding and a $140M partnership with Sanofi. Join us if you're excited to shape the future of AI-driven drug discovery, and want your code to change the course of real diseases.