Neural Network Performance Engineer

Here at Humanoid, we believe in a future where robots amplify human potential. That's why we've set out on a mission to build the world's most capable, commercially-scalable, and safe humanoid robots. We're bringing that mission to life with HMND-01 Alpha - our rapidly developed humanoid platform now running in real industrial pilots - and we're growing the team to take it even further., We're hiring a Neural Network Performance Engineer to join our VLA team based in London. In this role, you will work on all aspects of running capable neural-network based control policies at a high rate with minimal latency, both on cloud hardware and onboard. Your work will be critical to delivering smooth robot motions while reacting to environment changes as quickly as possible., * Analyze performance bottlenecks of a particular model architecture and come up with potential improvements.

• Make the model run on a new hardware (e.g. NVIDIA Thor) efficiently.
• Implement custom kernels to reduce memory throughput requirements where it matters.
• Quantize a model with minimal loss of quality.
• Suggest and implement changes of model architecture that will enable better performance characteristics without sacrificing model capabilities.

Do you have experience in Python?, * 3+ years building deep-learning systems (industry or research) with shipped models or published artifacts to show for it.

• 1+ years experience working on performance of neural network inference (analyzing bottlenecks, writing custom kernels, quantizing models, fighting deep learning compilers).

• Excellent understanding of GPU architecture and why some models run faster than others.

• Strong Python + PyTorch/JAX; you can profile, debug numerics, and write maintainable research code.

• You document experiments clearly and communicate trade-offs crisply. Nice to have:

• Robotics or autonomous driving experience.

• Open source code showcasing your ability to improve inference performance.

• Publications at ICLR/ICML/NeurIPS or equivalent open-source contributions.

• Familiarity with vision-language (VLM) or vision-language-action (VLA) models.

• Meaningful time off to rest and recharge: 23 days of annual leave (accrued), 15 days of paid sick leave, and paid company holidays.
• Fully funded private healthcare for UK employees, with broad provider access, virtual and in-person care, and strong mental health and serious illness support.
• Equity included-we believe builders should share in what they build.
• Pension scheme with a total 8% contribution (5% employee, 3% employer) on full earnings.
• Free daily breakfast, catered lunch, and snacks in-office.
• Collaboration with top-tier engineers, researchers, and product experts in AI and robotics.
• Freedom to influence the product and own key initiatives.