Edge AI Engineer in Oxford

A once in a lifetime opportunity has arisen for an Edge AI Engineer to have a major impact in the development of next generation wireless communications which will revolutionise several key industries.

If you really want to contribute to future technology, and AI, Data Science, or Machine Learning is your passion then this early stage, fast paced, and independently funded start up wants to hear from you. Led by an incredibly talented team of industry experts, and with strong links to the University of Oxford, they are on a mission to enable safe and efficient communication systems which will ultimately protect our way of life. By joining them, you will create a substantial impact by developing critical technology that will save lives and ensure our society remains safe in an ever-changing world.

Key responsibilities:

• Designing and optimising ML models to enhance secure communications and signal processing on a range of edge devices.
• Implementing low-latency, high-performance deep learning pipelines on hardware accelerators such as FPGA, TPU, and ASICs.
• Optimising CNN, Transformer, RNN, and/or GNN architectures for deployment on low-power embedded systems.
• Applying quantisation, pruning, distillation, and model compression to enhance efficiency.
• Strengthening model robustness against adversarial attacks and system-level security threats.
• Collaborating with embedded and security engineers to align AI performance with real-world system constraints.

Essential experience & skills:

• Master's or Ph.D. (or equivalent experience) in Data Science, Machine Learning, Artificial Intelligence, or a related field.
• Strong proficiency in Python with practical experience of PyTorch or TensorFlow.
• Working knowledge of implementing and optimising deep neural networks (e.g. CNNs, Transformers, GNNs).
• Hands-on experience with embedded C/C++ for model integration with an understanding of low-latency and low-power constraints in real-time systems.
• Awareness of adversarial ML and model robustness techniques.
• Understanding of secure-by-design principles and trusted execution concepts for AI on edge devices.
• Keenness to work on meaningful problems within the context of UK Defence and Security.

Desirable experience & skills:

• 5+ years of experience in AI/ML systems development.
• Understanding of training-inference workflows, including data preprocessing, model evaluation and benchmarking.
• Familiarity with hardware accelerators (FPGA, TPU, ASIC, GPU-based inference).
• Experience with model optimisation techniques: quantisation, pruning, knowledge distillation and model compression.
• Proficient with Git, CI/CD and Linux-based development environments.
• Ability to document and test code for reproducibility and maintenance.

If you have experience working on Edge AI and you have a deep passion for AI, Data Science and Machine Learning, then our wireless communications start up wants to hear from you.