Machine Learning Engineer (ID: rFnUoQE7)

We are looking for a Machine Learning Engineer to join the team and help push the boundaries of AI for electronic design automation (EDA). You will develop, optimize, and deploy cutting-edge machine learning and reinforcement learning models focused on automating complex PCB design problems, working closely with researchers and engineers to bring ideas to life.

Machine Learning Engineer Responsibilities:

• 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.

Requirements:

• B.Sc., M.Sc., or Ph.D. in Computer Science, Machine Learning, Electrical Engineering, or a related technical field.
• 2–5 years of professional experience in applied machine learning or engineering role.
• 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.

Nice to have:

• 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.

About Us:

DeepPCB is our AI-powered Place & Route PCB (Printed Circuit Board) design tool. We use a combination of deep reinforcement learning and high-performance computing to automate and scale PCB place-and-route workflows, accelerating hardware innovation globally.

Founded in 2014, we are a pioneering AI company at the forefront of innovation. With strategic offices in major cities worldwide, including London, Paris, Berlin, Tunis, Kigali, Cape Town, Boston, and San Francisco, we collaborate with giants like Google DeepMind and prestigious educational institutions like MIT, Stanford, Oxford, UCL, and Imperial College London. We are a Google Cloud Partner and a select NVIDIA Elite Service Delivery Partner. We have been listed among notable players in AI, fast-growing companies, and Europe's 1000 fastest-growing companies in 2022 by Statista and the Financial Times. Our recent acquisition by BioNTech has further solidified our commitment to leading the industry.

Our commitment to our people

We empower individuals to celebrate their uniqueness here with us. Our team comes from all walks of life, and we’re proud to continue encouraging and supporting applicants from underrepresented groups across the globe. Our commitment to creating an authentic environment comes from our ability to learn and grow from our diversity, and how better to experience this than by joining our team? We operate on a hybrid work model with guidance to work at the office 3 days per week to encourage close collaboration and innovation. We are continuing to review the situation with the well-being of our employees at the forefront of our minds.

Right to work: Please note that you will require the legal right to work in the location you are applying for.

Position: Machine Learning Engineer  -  Salary: £60,000 TO £80,000 Per Year  -  Location: London / Hybrid / 3 Days in the Office