Research Engineer
London
InstaDeep
InstaDeep delivers AI-powered decision-making systems for the Enterprise. With expertise in both machine intelligence research and concrete business deployments, we provide a competitive advantage to our customers in an AI-first world.Join us to be a part of the AI revolution!
About DeepPCB:DeepPCB is InstaDeep’s 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.Learn more at deeppcb.ai.
Role Overview:We are looking for a Research Engineer to join the DeepPCB team and push the boundaries of AI for electronic design automation (EDA). You will design, implement, and deploy state-of-the-art machine learning and reinforcement learning algorithms for real-world PCB design problems, helping define the future of hardware engineering.
Responsibilities
- Research, design, and implement scalable deep learning and reinforcement learning algorithms for PCB place and route challenges.
- Adapt and optimize ML algorithms for high-performance environments (e.g., distributed clusters, GPUs).
- Build and deliver production-grade ML systems and proofs-of-concept that integrate into the DeepPCB product platform.
- Report and present your research and development work internally and externally, tailoring communication to technical and non-technical audiences.
- Collaborate cross-functionally with AI researchers, engineers, product managers, and business development teams.
- Represent DeepPCB at technical conferences, customer meetings, and other events when needed.
Requirements
- B.Sc, M.Sc or Ph.D. in Computer Science, Machine Learning, Reinforcement Learning, Electrical Engineering, or a related field.
- 2–5 years of experience in research, engineering, or applied machine learning roles.
- Strong background in Machine Learning, Deep Learning, and ideally Reinforcement Learning.
- Proficiency in Python and modern ML libraries (TensorFlow, PyTorch, JAX, or Keras).
- Solid understanding of and experience with version control workflows (GitHub, GitLab) and clean coding practices. Experience with CI/CD pipelines to automate the building, testing, and deployment of ML projects.
- Ability to work in a fast-paced and highly collaborative environment.
Nice to haves
- 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.
Right to work: Please note that you will require the legal right to work in the location you are applying for.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: CI/CD Computer Science Computer Vision Deep Learning EDA Engineering GCP GitHub GitLab Google Cloud JAX Keras Kubernetes Machine Learning Open Source Pipelines Python PyTorch Reinforcement Learning Research TensorFlow Testing
Perks/benefits: Conferences Team events
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