Senior AI Engineer (Autonomy & Machine Learning)

Overview

In this AI Engineer role you apply AI/ML to solve safety-critical, real-world challenges in defence and aerospace. You will design, build and deploy robust AI capabilities across a multidisciplinary team, from concept to production in mission-critical environments. The work spans autonomy, computer vision, NLP and data-driven systems, with a focus on secure, explainable solutions. You’ll collaborate across engineering domains to deliver impactful AI components and demonstrable results for customers.

Pay / Benefits

• Private Medical Insurance
• Cycle & Tech Scheme
• Employee assistance programme
• Life insurance & Pension Scheme
• Social atmosphere, team events
• Flexible working (role dependent)

Responsibilities

• Design and develop AI/ML solutions for complex business and engineering challenges
• Translate requirements into scalable AI architectures and measurable outcomes
• Train, evaluate and optimise models across computer vision, NLP/LLMs, time-series and autonomous systems
• Build data processing pipelines with feature engineering, experiment tracking and model validation
• Collaborate with software, systems, cyber and data engineering teams to productionise AI
• Champion Responsible AI with security, safety, explainability and regulatory compliance
• Develop reusable AI components, frameworks and reference implementations
• Support technical demonstrations, bids, proofs of concept and customer workshops

Key requirements

• Strong Python development with PyTorch, TensorFlow, Scikit-Learn and Hugging Face
• Experience developing and deploying ML solutions including deep learning, CV, NLP/LLMs or time-series
• Experience with autonomy frameworks such as ROS2 and AI integration into autonomous systems
• Understanding of software engineering best practices: CI/CD, testing, version control, code quality
• Experience with data processing/analysis: Pandas, NumPy, SQL; model deployment: FastAPI, ONNX, TorchScript
• Commercial AI/ML development experience and deployment into operational environments
• Strong collaboration and stakeholder engagement skills
• Willingness to obtain security clearance (SC) if required

• Strong communication with technical and non-technical stakeholders
• Collaborative mindset within multidisciplinary teams
• Proactive, delivery-focused and influence-driven
• PyTorch
• TensorFlow
• Scikit-Learn

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