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If your ambition is to create the final interface which connects humans to machines then this is for you.

CEREBIONICS is building non-invasive brain-computer interfaces for robotic platforms.

We enable humans to control autonomous and robotic systems directly through neural signals — creating a new class of human-machine interaction for high-stakes environments. Our long-term mission is to build the universal human-machine interface, enabling direct neural control of any autonomous system. We’re starting with robotics because it’s the hardest and most demanding environment.

We are now hiring a founding machine learning engineer to build the intelligence layer of our platform and help shape the future of brain-computer interfaces.

📍 This role is based in London
🕒 Full-time position

What you'll do

- Build and deploy real-time machine learning models for brain-computer interfaces.
- Design, train, evaluate and improve models used in real-time environments.
- Own systems from prototype through deployment.

About you

- Deep interest in machine learning and a habit of staying at the frontier of new ideas and research.
- Experience building and deploying real ML systems into production.
- Strong engineering instincts and a willingness to be hands-on.
- You care about performance, robustness and real-world behavior.
- You want responsibility and technical ownership.
- You enjoy solving hard problems when there is no existing playbook.

Bonus if you have experience with:
- Signal processing or biosignals.
- Robotics, control systems or edge deployment.

What you'll get

- Founding role with deep technical ownership
- Competitive compensation (salary + equity)
- Direct influence over product, architecture and direction
- Join Project Europe co-works every 3 months with top founders and operators
- Work on frontier technology at the intersection of neuroscience, robotics and AI

Want to join the mission?

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What long-term future motivates you to work with neurotech and robotics?

What is something you've built that you're proud of?

Tell us about a time you had to make a difficult technical decision. What constraints did you work under and how did you decide?

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Questions? please reach out to [email protected]