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MiddleOfficeLondon

Deep Learning Engineer

H
Humanoid
Уровень
Middle
Формат
Office
О роли

Описание вакансии

About the company
  • Humanoid is building the world's most capable, commercially-scalable, and safe humanoid robots.
  • HMND-01 Alpha is a rapidly developed humanoid platform now running in real industrial pilots.
Responsibilities
  • Post-train policies via behaviour cloning and RL; own the full loop from data to deployment.
  • Partner with the Data Collection team to drive collecting new data: specify what good data looks like, identify failure modes, ensure diversity and coverage.
  • Work closely with external partners to ensure steady supply of high-quality pretraining-scale data.
  • Run pre-/mid-/post-training on VLA stack; explore new modalities and architecture changes.
  • Build and maintain continuous pipelines: ingest synthetic data and teleop logs, version them, apply weak-supervision labelling, curate balanced datasets, and auto-surface fresh failure cases into retraining.
  • Work with MLOps & Data Platform teams to scale distributed training and optimize models for real-time edge inference.
Requirements
  • 3+ years building deep-learning systems (industry or research) with shipped models or published artifacts.
  • Deep hands-on experience with at least one of: LLMs, VLMs, or image/video generative models — architecture, training, and inference.
  • Experience with deep learning infrastructure: streaming datasets, checkpointing & state management, distributed training strategies.
  • Strong Python + PyTorch/JAX; ability to profile, debug numerics, and write maintainable research code.
  • Familiarity with modern software engineering practices.
  • Clear documentation of experiments and crisp communication of trade-offs.
Nice to have
  • Robotics or autonomous driving experience.
  • Experience applying RL to LLMs or robotics.
  • Experience with VLA (vision-language-action) models.
  • Proven productization of deep nets (latency/throughput constraints, telemetry, on-device optimization).
  • Publications at top-tier deep learning conferences or equivalent open-source contributions.
  • Familiarity with OpenVLA, Physical Intelligence (π) models, or similar open source VLA frameworks.
Conditions
  • 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 with world-class engineers, researchers, and product experts.
  • Real ownership with direct access to founding leadership.
Стек и навыки

С чем работаем