Senior Machine Learning Engineer

Design, train, and deploy production-grade ML models.

As a Senior Machine Learning Engineer, you will lead the design, development, and deployment of production-grade machine learning systems for global enterprise clients. You'll work at the intersection of research and engineering, translating cutting‑edge papers into scalable, reliable solutions. This is a high‑impact role where you'll mentor junior engineers, shape our ML architecture, and collaborate directly with clients to solve their most complex challenges.

• Design and implement end-to-end ML pipelines from experimentation to production
• Lead model development across NLP, computer vision, and time‑series forecasting
• Architect scalable model serving infrastructure on cloud platforms (AWS/GCP/Azure)
• Conduct rigorous model evaluation, A/B testing, and performance monitoring
• Mentor junior ML engineers and conduct technical code reviews
• Collaborate with data engineers to optimise feature stores and data pipelines
• Stay current with latest ML research and evaluate applicability to client projects

• 5+ years of experience in machine learning engineering or applied ML research
• Strong proficiency in Python, PyTorch or Tensor Flow, and Scikit-learn
• Experience deploying ML models at scale using Docker, Kubernetes, or serverless
• Deep understanding of ML fundamentals: optimisation, regularisation, evaluation metrics
• Experience with cloud ML services (Sage Maker, Vertex AI, or Azure ML)
• Strong software engineering practices: version control, testing, CI/CD
• MSc or PhD in Computer Science, Machine Learning, or related field

• Published research in top ML venues (NeurIPS, ICML, ACL, CVPR).
• Experience with MLOps tools: MLflow, Weights & Biases, DVC.
• Familiarity with distributed training frameworks (Deep Speed, Horovod).
• Experience with LLM fine-tuning and prompt engineering.
• Contributions to open-source ML projects.

• Competitive salary with annual performance bonus.
• £2,000 annual conference and learning budget.
• Private healthcare and dental cover.
• Hybrid working — flexible office/remote split.
• 30 days annual leave plus bank holidays.
• Stock option scheme and pension matching.
• Latest hardware (M-series Mac Book Pro, GPU workstation access).

Our AI Research team is a tight‑knit group of 8 researchers and engineers passionate about pushing the boundaries of applied AI. We publish at top venues, contribute to open-source, and work on problems spanning healthcare diagnostics, financial risk modelling, and autonomous systems. You'll have the freedom to explore new ideas while delivering real value to clients.