humanoid - Software Engineer - Data & Sensors
Requirements
• Experience with 6-DOF pose tracking systems (VIO, optical trackers, or similar) and their common failure modes • Familiarity with ML training data formats and what an AI team actually needs from a recorded episode - understanding the consumer of the data you produce • Exposure to operator-facing tooling for data collection: session management, per-episode quality summaries, rejection and retry workflows • Experience scaling device software from a small number of prototype units to many devices operated by non-engineers in the field
Responsibilities
• Develop and maintain device software across the full episode lifecycle: session initialisation, per-sensor stream management, episode recording, and graceful shutdown • Integrate and synchronise sensor streams - wrist and head cameras, 6-DOF pose trackers, gripper aperture encoders, and optionally force/torque sensors - into temporally-aligned, policy-consumable trajectories • Define and maintain the data contract between UMI devices and the AI team: stream formats, episode packaging, metadata schemas, and the interface between raw recordings and training pipelines • Build and maintain data validation tooling that detects dropped frames, timing jitter, pose tracking loss, image quality degradation, and sensor faults before corrupt episodes enter the training dataset • Own operator-facing device software: status indication, start/stop/cancel episode controls, and clear feedback when a session needs to be retried • Support field data collection sessions - deploying devices to operators, validating data quality in situ, and iterating quickly when issues surface during collection • Debug integration failures on device hardware: camera driver issues, bus bandwidth saturation, tracker calibration drift, compute thermal throttling, and storage write failures mid-episode • WE’RE LOOKING FOR: • Experience in embedded or device-level software in a robotics or sensing context - writing code that runs on the device, not just talking to it • Proficiency in C++ and/or Python for real-time sensor drivers, inter-process communication, and data recording pipelines • Solid understanding of multi-modal sensor synchronisation - timestamps, hardware triggers, clock drift - and the practical consequences of getting it wrong for downstream ML • Familiarity with camera pipelines and the difference between what a sensor reports and what actually lands on disk with correct timing • Strong instincts around data quality and dataset hygiene - you are uncomfortable shipping episodes with frame drops, tracking loss, or misaligned streams • Proven ability to debug on real hardware: you read logs, attach profilers, and can diagnose whether a problem is a driver, a bus, or a timing issue
Benefits
• 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.
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