Luxoft

Project description This opening is for an ADAS Domain Controller project for a prestigious OEM, where Luxoft is working with the OEM teams to deliver next-generation Platform solution based on AUTOSAR Classic, AUTOSAR Adaptive and QNX working together as a system interacting with a host of cameras, ultrasound sensors, internal and external Radars. Luxoft is collaborating on Signal and Service Management, Diagnostics, SW Update, Vehicle Config, QNX/Middleware and Software Architecture areas with the OEM directly. Luxoft is expected to delivery quality and expert support in the above areas, drive topics independently, liaise with other OEM stake holders to remove blockers. The ideal candidate needs to have endless curiosity and can pair a global mindset with locally relevant execution. You should be a gritty problem solver, never give up attitude and self-starter who can think of out-of-box solution. The successful candidate will be a team player, display a balance of hard and soft skills, including the ability to respond quickly to Client's changing needs. Responsibilities Development of software architecture concepts for embedded systems Design, creation and implementation of software requirements Design, creation and implementation of software architectures Definition and verification of application/compliance with software guidelines for software requirements and software architecture Development of complex software components in programming languages such as C/C++ Creation of software specifications for suppliers and software specifications for customers Evaluation of internally and externally supplied software components and documentation Support in the specialist analysis and evaluation of customer requirements (RFI, RFQ) Support in the continuous improvement process for SWE1-SWE5 Coaching new employees Definition and design of the cyber security architecture according to ISO/SAE 21434 Participation in the selection of suitable components, such as system-on-chips or microcontrollers Support with software integration tests Collaboration with the Development and maintenance of the hardware-software interface (HSI) according to ISO 26262 Support with criticality analyses according to ISO 26262 Must have At least 5 years of professional experience with complex embedded software projects in the automotive industry (SW development, coding(C/C++), etc.) At least 3-5 years of professional experience in creating software architecture and software requirements Experience with multi-core controllers from Renesas, TI, Infineon etc. In-depth knowledge of AUTOSAR Very good knowledge of software architecture for embedded systems (e.g. AUTOSAR, RTOS) In-depth knowledge of relevant standards, including Automotive SPICE, ISO 26262, ISO 21434 and ISO 16505 Excellent programming skills in high-level languages such as C/C++ Knowledge of low-level programming and hardware-related programming Very good knowledge of the communication protocols CAN, SPI, I2C and UART 3+ years' experience in Adaptive Autosar based software development and Architecture 3+ years in C++ Strong understanding of Classic and Adaptive software clusters Experience in SOME/IP network binding Strong experience working with PREEvision for SoA modelling Strong knowledge of PREEvsion metamodel Nice to have ECU Calibration IPC Communication Ethernet Stack Automotive Safety

Overview Project description We are seeking a skilled Machine Learning Engineer to develop and deploy Graph Neural Network (GNN) based surrogate models that approximate complex physics simulations for oil & gas pipeline and well networks. This is a hands-on role for someone who can build high-fidelity neural network models that replace computationally expensive reservoir and network simulators (Nexus, Prosper). Responsibilities Design and implement Neural Network architectures to model flow dynamics in interconnected pipeline networks Build surrogate models that accurately predict pressure distributions, flow rates, and network behavior under varying operational scenarios (training data is acquired through running simulations of the physics models) Create data pipelines to extract network topology and simulation results from physics-based models (Nexus/Prosper) and transform them into graph representations Develop training frameworks that incorporate physics constraints (conservation laws, pressure-flow relationships) into neural network loss functions Collaborate with petroleum engineers to ensure model predictions align with physical behavior and operational constraints Implement model monitoring, validation, and continuous improvement workflows Business trip to Kuwait for first 6-12 months. On-site Skills Must have Strong expertise in Graph Neural Networks (GCN, GraphSAGE, Message Passing Networks) with proven implementation experience Deep understanding of deep learning frameworks (PyTorch Geometric, DGL, or TensorFlow GNN) Experience building surrogate models or physics-informed neural networks (PINNs) for engineering applications Proficiency in Python and scientific computing libraries (NumPy, SciPy, Pandas) Demonstrated ability to work with complex data structures (graphs, time-series, spatial data) Understanding of optimization techniques and handling large-scale training data Understanding of graph theory and network analysis Experience with data structures and graph representations (adjacency matrices, edge lists, sparse tensors) Knowledge of hyperparameter tuning, model building and uncertainty quantification in ML models Ready for a long term business trip to Kuwait for first 6-12 months Nice to have Background in petroleum engineering, process engineering, or fluid dynamics; Familiarity with reservoir simulation or pipeline hydraulics; Experience with MLOps practices and model lifecycle management; Publications or open-source contributions in graph ML; Experience deploying ML models in production cloud environments (containerization, API development); Industry experience in Oil & Gas is a strong plus, however candidates with relevant surrogate modeling experience from other engineering domains are encouraged to apply. Education Educational Background: MS/PhD in Computer Science, Computational Engineering, Applied Mathematics, or related field preferred; Strong mathematical foundation in linear algebra, graph theory, and numerical methods; Understanding of graph theory and network analysis

A leading technology firm is looking for a skilled Machine Learning Engineer to develop advanced Graph Neural Network models for oil & gas applications. The role involves designing neural networks, building predictive models, and collaborating with engineers. Candidates should hold an MS/PhD in relevant fields and have deep expertise in Graph Neural Networks, alongside strong Python skills. This position requires a business trip to Kuwait for the initial months and aims at significant contributions to advanced engineering projects.

A leading technology firm in Greater London seeks an experienced Database Engineer to support its relational database platforms. Ideal candidates will have 10-15 years as an Oracle DBA and expertise in Exadata infrastructure. You will develop automation tools, support application teams, and manage performance tuning and backup strategies. Collaborate in a dynamic environment where creativity and friendship thrive. This position requires strong skills in Oracle databases and good knowledge of English; German is a plus.

Project description Luxoft is working on an ADAS Domain Controller project for a prestigious OEM, working closely with the OEM teams to deliver next generation Platform solutions based on AUTOSAR Classic, AUTOSAR Adaptive, and QNX working together as a system interacting with a host of cameras, ultrasound sensors, internal and external Radars.At Luxoft we are looking for experienced team members who deliver quality and expert support by being involved in AUTOSAR Classic Platform Configuration, Integration, and Release Management willing to take full responsibility for the deliverables and willing to support our customer in the development of the next generation system.The ideal candidate needs to have endless curiosity and can pair a global mindset with locally relevant execution. You should be a gritty problem solver, never give up attitude and self starter who can think of out of box solution. The successful candidate will be a team player, and display a balance of hard and soft skills, including the ability to respond quickly to the Client's changing needs. Responsibilities Relevant Degree, Appropriate professional body membership and/or relevant experienceProven record in designing and architecting complex, safety critical embedded systems, inlcuding but not limited to: life cycle management, power architecture, SoC/MCU/peripheral communication and fault handlingSystem Architecture Design: Expertise in designing scalable, secure, safe, efficient embedded systems.Real Time Systems: Experience with deterministic systems and timing constraints.Microcontroller & SoC Knowledge: Deep understanding of ARM, RISC V, NVidia and other architectures.Understanding of industry standard software architecture solutions(Adaptive & Classic AUTOSAR stacks), operating systems and their configuration (e.g. QNX, Linux, Android)Expert level of competence in all aspects of Model Based Systems eEngineering (MBSE): concept design, requirements authoring, logical and solution architecture, quality and legal activitiesCompetent in system and SW modelling (SysML / UML, ideally in MSOSA tool)COmpetent in SDLC and Integration e.g Git, Ci/CD, debugging and an advantage would e gained with experienced in developing "Architecture as code"Proven knowledge of Driver Assistance Systems or associated technology (Computer Vision, Image processing, Machine learning, Path planning, Sensor Fusion, Vehicle Dynamics + Control)Ability to rapidly understand the key concepts of the system of interest and to lead groups of SME's to design and architect these systemsAbility to resolve complex, cross functional and cross-domain systems engineering problemsProven ability to develop architectural solutions appropriately balancing technical and non technical criteriaUnderstanding of Functional Safety (ISO 26262), Cyber Security (ISO 21434), GDPR, MISRA and quality techniques. SKILLS Must have Experience of developing and delivering embedded systems or ECUs, ideally in an automotive tier 1 environmentExperience teaching/coaching/mentoring of engineers, peers and seniors in systems engineering techniques.Competent requirements author (ideally TRM, or other requirements management tools)Understanding of programming languages, AI and Machine Learning, "Archictecture as code"Understanding of closed loop control systems physical architectures including sensors, actuatorsKnowledge and practice of Agile techniques, especially in the context of defining solution architectures in an agile contextThe main skills needed by a System Architect are: Knowledge of the System Architectural Design procedures established in the organization and project. Knowledge of the traceability procedures Knowledge of the Requirements management tools used in the organization & project (i.e. DOORS) Knowledge of the Requirements management system & strategy established in the project Knowledge of the change management tools used in the organization & project (i.e. ALM) Knowledge of the problem resolution tools used in the organization & project (i.e. ALM) Knowledge of System Architecture Design methodology and best practices Knowledge of the Functional Safety procedures & techniques established in the organization and project. Knowledge of Adaptive & Classic AUTOSAR stacks Knowledge of the ISO 26262 standard Knowledge of the FMEA Method Knowledge of the FTA Method Knowledge of Hazard analysis and risk evaluation methods Knowledge of the ISO 21434 standard knowledge of the cybersecurity procedures & techniques established in the organization and project Soft Skills Analytic thinking Empathy Communication skills Methodical Self-confident and persuasiveness Conflict Resolution skills Moderation skills Nice to have ASPICE methodologyAgile methodologySoftware Development experience