Staff Autonomy Engineer

San FranciscoFull Timelead

OtherAutonomy Engineer

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Quick Summary

Overview

Chef Robotics is on a mission to accelerate the advent of intelligent machines in the physical world, starting with food.

Technical Tools

OtherAutonomy Engineer

Chef Robotics is on a mission to accelerate the advent of intelligent machines in the physical world, starting with food. We build AI-powered robots that assemble fresh meals at scale for some of the largest food producers in North America — companies making ready-to-eat meals for airlines, retailers, meal kits, and the frozen food aisle.

Our robots operate in high-mix, high-variability production environments where ingredients change shape, color, and consistency from one tray to the next. Solving this requires tightly coupled perception, manipulation, and learning — and a team that ships hardware-software systems into customer facilities and keeps them running.

Headquartered in San Francisco, we are a venture-backed team of robotics, ML, and operations engineers building the foundation for general-purpose food robotics.

About the Role

As a Staff Autonomy Engineer, you will own the technical architecture of Chef's autonomy stack end-to-end — from perception and action prediction through closed-loop control and production deployment. This is a hands-on technical leadership role: expect to spend the majority of your time designing and building, with the remainder setting direction, mentoring engineers, and driving cross-functional alignment. You will report directly to the engineering leadership and have direct influence over how Chef's autonomy systems scale across a growing commercial fleet.

We are a small, high-ownership team. We work onsite five days a week and move with startup urgency.

Own the end-to-end architecture and hands-on development of Chef's autonomy stack — perception, action prediction, closed-loop control, and sensor fusion — from prototype through production deployment

Design and implement learning-based systems that predict and execute robot actions from visual and operational observations, generalizing across diverse ingredient types with minimal per-item tuning

Build closed-loop control systems that integrate vision, weight feedback, force-torque sensing, and trajectory planning for robust real-world manipulation

Develop rapid onboarding capabilities — algorithms and tooling that enable new meal types and ingredient configurations to be deployed quickly from minimal demonstrations

Instrument autonomy systems for production monitoring, failure detection, and continuous improvement; build data collection pipelines that feed back into model retraining

Define objective qualification criteria for autonomy subsystems; drive reliability and performance improvements using production data across the deployed fleet

Investigate and integrate the latest advances in robot learning, foundation models, and manipulation research — continuously evaluating what's ready to move from research into production

Mentor senior engineers, lead design reviews, and help build a team capable of scaling Chef's autonomy stack to hundreds of deployed systems

Demonstrated experience shipping a complete autonomy or manipulation system to real-world deployment — not just simulation or research prototypes

Deep technical expertise across at least two of: perception systems, visuomotor control, action prediction, sensor fusion, or motion planning

Strong software engineering fundamentals in Python and C++; experience building production-quality, maintainable systems across research and deployment codebases

Track record of technical leadership: driving architecture decisions, leading cross-functional projects, and raising the engineering bar on a team

Comfort with ambiguity and urgency — able to set direction and execute in a fast-moving startup environment

Experience with food, agricultural, or consumer goods robotics where object variability is high

Experience with ML frameworks (PyTorch preferred) and the full model lifecycle — training, evaluation, deployment, and field iteration

Familiarity with foundation model approaches for manipulation: diffusion policies, VLAs, world models, JEPA-style architectures

Background in sim-to-real transfer, domain randomization, or synthetic data generation for manipulation

Experience with ROS and real-time robotics middleware

Prior startup technical leadership experience