Our client is a pioneering technology company delivering laser communications and temporospatial software-defined networking platforms to the aerospace and space industry. Leveraging technology originally developed at a major global tech firm, they are leading innovation in satellite, airborne, cislunar, and deep-space mesh networks. They are transforming how planetary-scale networks are orchestrated and managed across land, sea, air, and space. The Role Our client is looking for a Machine Learning Engineer to join their Spacetime team. This is a hybrid role combining ML research and engineering, focused on solving some of the most complex temporospatial networking and resource management problems in the industry. Youll work at the cutting edge of AI-driven networking and space systems, collaborating with engineers, researchers, and customers globally. Key Responsibilities Research and develop state-of-the-art ML algorithms for network orchestration Build and manage ML training infrastructure using Kubernetes and MLOps tools Develop and maintain documentation for new algorithms and systems Integrate AI/ML solutions into the wider Spacetime platform Act as a technical expert when engaging with customers on ML technologies Required Skills & Experience MSc or PhD in Computer Science, Machine Learning, Mathematics, Statistics, or similar Strong Python programming skills Experience with PyTorch, TensorFlow, or optimisation libraries (e.g. Gurobi, OR-Tools) Strong technical communication and stakeholder engagement skills Ability to write clean, efficient, maintainable code Interest in explaining and presenting complex technology Desirable Experience in satellite, wireless communications, or software-defined networking Background in technical sales or customer-facing engineering roles Experience writing tests for ML systems Experience with C, C++, or Go Whats On Offer Remote working within the UK Competitive salary pension private health insurance equity Work on world-leading space and AI technology High-impact projects in space-ground integration and AI-driven networks Collaborative, international research environment