About the RoleWere seeking an AI/ML Engineer to build and deploy learning-driven capabilities within our autonomous space systems. In this role, youll create models that directly operate in closed-loop autonomy, supporting perception, navigation, and decision-making in real mission environments. This is a hands-on position for engineers who want their models running on real spacecraft, not just evaluated in offline experiments.Job DescriptionDesign, train, and validate AI/ML models supporting satellite autonomy, including rendezvous and proximity operations, on-orbit inspection, formation flying, and space domain awareness.Develop learning-based components for guidance, navigation, perception, and decision-making, such as pose estimation, anomaly detection, behaviour recognition, and trajectory generation.Build LLM- and VLM-powered tools to enable intuitive satellite operations, including natural language command interfaces and visual scene understanding.Create and maintain synthetic data generation pipelines that model realistic orbital dynamics, sensor behaviour, lighting conditions, and uncertainty, using domain randomization and sim-to-real techniques.Extend and improve simulation environments used for training, verification, stress testing, and adversarial evaluation of autonomy models.Optimize models for flight deployment, applying techniques such as quantization, pruning, batching, and real-time inference on limited onboard compute.Integrate ML components into flight software using well-structured Python and C++ interfaces, with strong safeguards and fallback behaviours.Participate in software-in-the-loop and hardware-in-the-loop testing, closing the feedback loop between simulation, sensors, control systems, and model improvements.Take full ownership of your models, from early experimentation and training pipelines to testing, review, deployment, and long-term maintenance.RequirementsStrong foundation in machine learning, deep learning, reinforcement learning, or a related technical discipline.Practical experience developing, training, and evaluating ML models for perception, estimation, planning, or control systems.Proficiency with modern ML frameworks such as PyTorch or TensorFlow, and the ability to integrate models into Python and C++ systems.Experience building simulation tools or data generation pipelines to support ML development.Ability to design, debug, and scale training workflows, including dataset management, distributed training, and evaluation.Familiarity with deploying ML inference as part of larger autonomous or robotic software stacks.A sense of ownership, adaptability in fast-paced environments, and clear communication around technical tradeoffs.Nice to HaveExperience working with foundation models or large-scale pretrained architectures.Knowledge of orbital mechanics, spacecraft dynamics, or space systems.Experience combining learned models with classical estimation, guidance, or control algorithms.Background in sim-to-real transfer, domain adaptation, or operational ML systems.Exposure to embedded inference, GPU optimization, or real-time autonomous platforms.Publications, open-source contributions, or research experience in ML, robotics, autonomy, or reinforcement learning.What we offerThe opportunity to be part of an international team transforming the space industry.A creative and innovative work environment where ideas turn into reality.Competitive salary and benefits.