Tech Lead, Companion

1X Technologies ASPalo Alto, CA
19d

About The Position

About the Role NEO is a home robot that handles chores and provides personalized assistance. Companion Mode is how people actually live with NEO: natural voice interaction, contextual help based on what NEO sees, and a personality that belongs in your home. As Tech Lead, you own the end-to-end Companion experience. You'll lead a small, senior team of engineers and HRI designers, stay hands-on, and ship consistently. This role is critical to scaling NEO as a product - it is the customer’s first impression of NEO and 1X and is one of the highest impact roles at the company.

Requirements

  • Have 5+ years building user-facing products that must work every day: consumer hardware, robotics, AR/VR, voice assistants, or similarly unforgiving domains.
  • Have hands-on experience with speech ML (ASR, TTS, emotion detection, speaker diarization, or multimodal input) and understand latency/quality tradeoffs at a systems level.
  • Are familiar with Python and/or C++ and writing and deploying code across different environments.
  • Understand full-stack product development, from Docker deployment to Python prototyping with LiveKit.
  • Have strong product taste: you can look at an interaction and know whether it will delight or confuse, and you back it up with data and iteration.

Responsibilities

  • Own Companion Mode architecture, execution, and delivery across the full user journey: multimodal social perception, robot behavior, feedback, and memory.
  • Build context into interaction by fusing perception, spatial understanding, and memory so NEO can provide relevant, personalized help.
  • Lead a cross-functional pod and set research direction and make taste choices.
  • Interface with the rest of NEO (autonomy, teleop workflows, app surfaces, on-robot systems) to make Companion a cohesive experience.
  • Build and deploy production speech models (ASR, TTS, and/or Speech to Speech).
  • Own the full pipeline from data collection and model training through deployment and monitoring.
  • Solve hard acoustic problems that come with putting a robot in someone's living room: far-field recognition, noise robustness, barge-in handling, and multi-speaker environments.
  • Design voice interaction that feels human: natural prosody, appropriate turn-taking, responses that match context and emotional tone.
  • Build evaluation infrastructure, define quality metrics that actually correlate with user experience, and use real-world feedback to prioritize improvements.
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