Senior Applied Machine Learning / Computer Vision Engineer Oxford - hybrid working c£90-130k DoE Equity Were seeking a Senior Applied Machine Learning / Computer Vision Engineer to develop and deploy machine learning models for a cutting-edge multi-camera perception system. This is an opportunity to build real-world AI systems from first principles, combining research-level work with deployment and impact, with freedom to explore and contribute to publishable work. Founded in 2024 with a recently closed multi £million seed funding round, the business has a high-growth strategy that looks towards a series A in 18 months. Their technology is a real-time, high-resolution passive 3D sensor based on AI and multi-stereoscopy. For both defence and civilian use, the technology focuses on real-time 3D for supporting autonomous vehicles (UGV, UAV, USV), robotics and other such systems. Working closely with the AI Lead and CTO, you will take ownership of turning advanced models into robust, real-world components - from training pipelines through to deployment on edge systems. The Senior ML/CV Engineer role combines hands-on engineering with applied research, with opportunities to contribute to state-of-the-art work suitable for venues such as NeurIPS, ICCV, or CVPR, where appropriate. Responsibilities : Model Development & Training Develop and train models for perception, correspondence, and feature extraction Design experiments to improve performance, robustness, and generalisation Explore novel architectures and approaches where appropriate Data & Training Infrastructure Build and maintain scalable training pipelines Work with real-world and synthetic datasets Design evaluation frameworks and benchmarks Deployment & Optimisation Optimise models for edge and real-time deployment Improve inference speed, memory efficiency, and robustness Integrate models into full perception pipeline Applied Research Contribute to advancing the state-of-the-art in applied vision systems Collaborate on research outputs suitable for top-tier conferences Balance innovation with delivery constraints Requirements : PhD in Machine Learning, AI, Computer Vision, or related field Strong experience with deep learning frameworks (PyTorch / TensorFlow) Strong experience with computer vision models and ML training and evaluation pipelines Strong programming skills (Python, Java, C, CUDA and/or C++) Demonstrated ability to translate theory into working systems Citizenship of a NATO country (required due to project constraints) Highly Desirable: Publications in NeurIPS, CVPR, ICCV, etc. Experience deploying models to edge / embedded systems Experience with multi-view or 3D perception problems We encourage applications from researchers transitioning from academia; alternatively, you may already have significant industry experience.