Neural Network Performance Engineer

Job description

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. # About the Role 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. # What You'll Do - 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. # What We're Looking For - 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. # What We Offer - Competitive equity: stock options with meaningful upside as we scale. - 30+ paid days off, including 23 days of annual leave, all UK bank holidays, and additional company closure days (including Christmas–New Year shutdown). - Private healthcare, including virtual and in-person care. - Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings. - Free daily breakfast, catered lunch, and snacks in-office. - Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics. - Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.