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

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