
Senior Machine Learning Engineer
- London
- £80,000-100,000 per year
- Permanent
- Full-time
- Develop scalable and efficient machine learning algorithms to tackle PCB place-and-route challenges.
- Adapt and optimize ML models for large-scale distributed computing environments (e.g., GPUs, multi-node clusters).
- Build, test, and deploy robust production-level ML systems integrated into the DeepPCB platform.
- Collaborate with research scientists, software engineers, product managers, and business development teams.
- Clearly document and present your work internally and externally, adjusting technical depth based on the audience.
- Participate in technical discussions, design reviews, and customer-facing activities when required.
., ., or Ph.D. in Computer Science, Machine Learning, Electrical Engineering, or a related technical field. * 5 years of professional experience in applied machine learning or engineering roles.
- Strong expertise in Machine Learning and Deep Learning, with exposure to Reinforcement Learning as a plus.
- Proficiency in Python and modern ML libraries (e.g., TensorFlow, PyTorch, JAX, or Keras).
- Experience with version control systems (GitHub, GitLab) and knowledge of clean, maintainable coding practices.
- Familiarity with CI/CD pipelines for automating ML workflows.
- Ability to thrive in a fast-paced, collaborative, and dynamic environment.
- Prior experience with PCB design, EDA tools, or related optimization problems.
- Hands-on experience in high-performance computing environments (e.g., Kubernetes, Ray, Dask).
- Contributions to open-source projects, publications, or top placements in ML competitions (e.g., Kaggle).
- Expertise in related fields such as Computer Vision, Representation Learning, or Simulation Environments.