Machine Learning Engineer - Foundational

Harmattan AI

ABOUT US Harmattan AI is a next-generation defense prime building autonomous and scalable defense systems. Following the close of a $200M Series B, valuing the company at $1.4 billion, we are expanding our teams and capabilities to deliver mission-critical systems to allied forces. Our work is guided by clear values: building technologies with real-world impact, pursuing excellence in everything we do, setting ambitious goals, and taking on the hardest technical challenges. We operate in a demanding environment where rigor, ownership, and execution are expected. About the Role We are looking for a Machine Learning Engineer to join our Semantic Scene Understanding team in Paris. In this role, you will design the core algorithms to extract semantic information in real-time from the theatre of operations as seen through the different cameras of our different UAVs, to improve the operator’s scene understanding. Responsibilities * Design and Train: Develop state-of-the-art machine learning algorithms for semantic segmentation, object detection, and classification tailored to aerial imagery. * Advanced Feature Extraction: Build high-level tactical features on top of base semantic data, such as real-time road vectorization, trafficability analysis, and dynamic obstacle mapping. * Multi-Agent Fusion: Architect pipelines that temporally and spatially align semantic data from multiple moving UAVs into a cohesive Common Operational Picture (COP). * Edge Optimization: Optimize and deploy these algorithms directly into our tactical C2 platform, utilizing quantization, pruning, and hardware acceleration to meet strict real-time compute constraints. Candidate Requirements * Educational Background: MSc in Computer Science, Machine Learning, or a related field. A PhD is a strong plus. * Foundational Knowledge: Deep understanding of Machine Learning theory, Linear Algebra, and 3D-Geometry algorithms. * Core Tech Stack: Expert-level command of Python and deep learning frameworks (PyTorch). * Performance Engineering: Experience with C++ and inference optimization frameworks (e.g., TensorRT, ONNX Runtime, CUDA) is highly desirable. * Domain Experience (Plus): A track record of shipping CV/ML algorithms in production, particularly for edge/embedded systems or involving aerial (EO/IR) imagery. * Strong Ownership: Ability to take a feature from an ArXiv paper all the way to a ruggedized tactical PC. * Adaptability & Mission Focus: Thrives in a fast-paced startup environment and is 100% dedicated to building ethical defense technologies that bring a strategic edge to allied nations. Communication: Excellent verbal and written communication skills to collaborate effectively with software engineers and hardware teams. We look forward to hearing how you can help shape the future of autonomous defense systems at Harmattan AI.

Harmattan AI

ABOUT US Harmattan AI is a next-generation defense prime building autonomous and scalable defense systems. Following the close of a $200M Series B, valuing the company at $1.4 billion, we are expanding our teams and capabilities to deliver mission-critical systems to allied forces. Our work is guided by clear values: building technologies with real-world impact, pursuing excellence in everything we do, setting ambitious goals, and taking on the hardest technical challenges. We operate in a demanding environment where rigor, ownership, and execution are expected. ABOUT THE ROLE We are looking for a Computer Vision Engineer to join our Machine Learning and Computer Vision team. This role is crucial for developing core technical components across various robotics/aerospace projects. RESPONSIBILITIES * Research & Data Preparation: * Conduct research on state-of-the-art Computer Vision methodologies. Participate in the creation and curation of training and validation datasets. * Perform statistical analyses and develop visualization tools to ensure data quality. * Algorithm Development & Optimization: * Build and refine training pipelines and metrics to enhance model performance. * Develop and optimize Computer Vision algorithms for multiple robotics/aerospace projects. * Deployment & Integration: Implement ML/CV models into production-ready environments. Ensure seamless integration with Harmattan AI’s systems and conduct rigorous code reviews. * Validation & Monitoring: Test algorithms in real-world environments and develop monitoring tools. Track model performance and continuously improve deployed solutions. * Cross-Team Collaboration: Work closely with software and simulation teams to align development with system requirements. Communicate findings effectively to stakeholders. CANDIDATE REQUIREMENTS * Educational Background: A degree from a top-tier engineering school or university (Master’s degree in Computer Science or related field, PhD is a plus) * Technical Expertise: Strong mathematical foundations, coding skills (Python, C++ is a plus) and hands-on ML/CV project experience. Experience in top AI companies is a huge plus. * Passion for ML: Enthusiasm for Machine Learning and Computer Vision. * Strong Communication & Teamwork: Ability to collaborate effectively with diverse teams * Commitment: 100% dedication to Harmattan AI’s mission, vision, and ambitious growth plans, ready to go the extra mile to ensure operational excellence. We look forward to hearing how you can help shape the future of autonomous defense systems at Harmattan AI.

Proxima Fusion

WHO WE ARE Proxima Fusion is Europe’s fastest-growing fusion company and the continent’s best-funded fusion player, as well as the first spin-out from the Max Planck Institute for Plasma Physics (IPP). Backed by over €650M and powered by a growing team across Munich, Zurich, and Oxford, we are developing the hardware and infrastructure needed to deliver the world’s first commercial stellarator fusion power plant. Our concept advances the most mature fusion technology out there, the Wendelstein 7-X stellarator, through two next-generation machines: Alpha and Stellaris. Our work combines stellarator optimization, advanced computation, machine learning, and high-temperature superconducting magnets to unlock higher-performance designs that were previously out of reach. Turning these designs into a functioning fusion power plant requires excellence and ownership across every discipline, from physics and engineering to software, manufacturing, law, and business functions. TEAM AND ROLE * Architect a breakthrough energy technology – Play a defining role in designing and integrating the systems that will power the world’s first commercial stellarator fusion plant, influencing decisions that shape the future of clean energy. * Solve some of the most complex engineering challenges in fusion – Work across magnet design, HTS technology, manufacturing, structural integration, and controls, turning cutting-edge science into real hardware * Move fast and build what matters – Join a highly ambitious, multidisciplinary team that combines cutting-edge simulation with hands-on engineering, turning bold ideas into real hardware on the path to commercial fusion. WHY JOIN PROXIMA FUSION Impact: Your simulations will directly shape the magnets that enable commercial fusion energy. Ownership: As part of a small, highly technical team, you will define modeling standards and influence core design decisions. Frontier Engineering: Work at the intersection of high-field electromagnetics, cryogenics, and advanced numerical methods. Collaboration: Join a team combining deep superconducting expertise with advanced computational capability to solve one of the hardest engineering challenges of our time. YOUR IMPACT At Proxima Fusion, we are designing the first generation of fusion power plants to provide the world with clean, carbon-free energy. The heart of our reactor lies in its superconducting coils. These magnets operate at cryogenic temperatures, generate extreme magnetic fields, and must remain stable under complex electromagnetic and thermal transients. We are looking for a Numerical Modeling Engineer to develop high-fidelity simulation tools that predict and de-risk the behavior of our superconducting magnets. Your work will span electromagnetic, thermal, and transient multiphysics modeling - including quench dynamics - and will directly inform design decisions for conductors, coils, and protection systems. This role is not about running black-box simulations. It is about building robust numerical frameworks - combining commercial multiphysics tools with in-house developed models - to enable fast, reliable, physics-driven engineering decisions. WHAT YOU WILL DO Your work will combine physics modeling, numerical implementation, and close collaboration with magnet designers and experimental teams. You will contribute across three primary domains: 1. ELECTROMAGNETIC & THERMAL MULTIPHYSICS MODELING You will develop predictive models of superconducting magnet behavior across steady-state and transient regimes. * Electromagnetic Simulation: Model high-field magnet systems including current distribution, inductance, AC losses, and nonlinear material behavior. * Thermal Modeling: Simulate heat generation, conduction, and cryogenic cooling performance under operational and fault conditions. * Multiphysics Coupling: Develop coupled EM-thermal models to capture transient events such as current redistribution and localized heating. * Quench Modeling: Implement and validate numerical frameworks to simulate quench initiation, propagation, and protection strategies. * Model Validation: Correlate simulations with experimental data from conductor and coil tests to continuously refine predictive capability. 2. IN-HOUSE TOOL DEVELOPMENT & NUMERICAL INFRASTRUCTURE Beyond commercial software, you will help build Proxima’s internal modeling backbone. * Custom Solvers & Reduced-Order Models: Develop fast, scalable modeling tools for system-level studies and design iteration. * Automation & Parametric Studies: Build robust pipelines for design sweeps, optimization, and uncertainty quantification. * Code Development: Contribute to internal Python- or C++-based frameworks for magnet modeling and data post-processing. * Verification & Benchmarking: Establish numerical best practices, validation procedures, and cross-comparison between tools. * Scalability: Ensure models can scale from conductor-level physics to full magnet assemblies. Experience with COMSOL or similar commercial multiphysics tools (ANSYS, Opera, etc.) is valuable, but building reliable, physics-based in-house tools is equally (if not more) important. 3. DESIGN INTEGRATION & ENGINEERING DECISION SUPPORT Your models will not live in isolation — they will directly shape hardware. * Design Feedback: Provide quantitative guidance on conductor layout, stabilization strategies, and protection schemes. * Risk Assessment: Identify failure modes and quantify margins under realistic operating scenarios. * Cross-Team Collaboration: Work closely with magnet engineers, quench protection specialists, and test engineers. * Documentation & Communication: Translate complex physics into clear engineering recommendations. WHO YOU ARE We are looking for a rigorous numerical thinker who enjoys bridging fundamental physics and practical engineering. Background: * Degree (MSc or PhD) in Electrical Engineering, Applied Physics, Computational Engineering, or a related field. Core Expertise: * Strong foundation in electromagnetics and physics-based numerical modeling (e.g., FEM, nonlinear coupled systems), with the ability to implement and extend models programmatically * Experience with multiphysics and transient simulations (e.g., electromagnetic–thermal coupling, fast transients). * Proficiency in at least one scientific programming language (Python, MATLAB, C++, or similar), with interest in developing internal modeling tools and workflows. Valued Experience (not all required): * Electromagnetic numerical modeling * COMSOL or other commercial FEM tools. * Modeling of high-current or high-field devices. * Thermal modeling and heat transfer in complex systems. * Experience building internal engineering tools rather than relying purely on GUI-based workflows. Mindset: * You question assumptions and validate results critically. * You are comfortable building models from first principles. * You thrive in a startup environment where tools, processes, and standards are still evolving. Prior experience with superconductors or HTS magnets is a plus - but strong electromagnetic and numerical expertise is the primary requirement. INTERVIEW PROCESS * Recruiter Interview (30-60 min) * Technical Screening (30 min) * Technical Panel (3x60 min) *This role sits at L3 of our framework, please inquire during the recruitment process for further information. At Proxima Fusion, our mission is bold: making limitless clean energy a reality. To get there, we need a high-performing, diverse team that brings different perspectives, challenges assumptions, and builds together with purpose. We know that diversity of thought and experience leads to better ideas, stronger execution, and a more resilient team. We don’t look at how you identify, what you look like, who you choose to worship or what ethnicity you are. We care about what you can bring to the table.