Chef Robotics is accelerating the deployment of intelligent machines in the physical world starting with food production the sector facing the largest labor shortage in the U.S. with 1.14M unfilled jobs today and 3.1M projected by 2030. These roles cant be offshored making robotics essential to keeping production onshore and strengthening Americas manufacturing base.
Our AI-powered robots automate food prep and assembly in commercial kitchens and food manufacturing and have already produced over 110 million meals in production generating the worlds largest proprietary dataset for deformable food manipulation. Backed by investors including Kleiner Perkins Construct Bloomberg Beta and Promus Ventures and built by a team from Cruise Zoox Google Tesla and Amazon Robotics Chef is rapidly scaling with multiple multi-year contracts and a mission to put an intelligent robot in every commercial kitchen.
About the Role
Chef Robotics is building autonomous robots that work alongside humans in commercial food preparation environments. Manipulation is one of the hardest open problems in robotics and food makes it harder. Unlike structured industrial parts food items are deformable visually similar irregularly shaped and behave differently depending on temperature moisture and preparation state. At Chef were solving this in production every day across a growing menu of meal types and preparation configurations.
As a Senior ML Engineer Manipulation you will own the learning systems that enable our robots to reliably pick place and handle diverse food classes using multiple end effectors from suction grippers to multi-finger hands. You will work end-to-end: from defining data collection strategies and training policies to deploying and debugging those policies on physical robots in real environments.
We are a small high-ownership team. We work onsite five days a week and move with startup urgency.
In this role you will:
Design and train manipulation policies behavior cloning imitation learning and RL for dexterous food handling across diverse item classes and end effector types (suction parallel jaw multi-finger)
Implement and evaluate modern policy architectures (diffusion policies transformer-based action models action chunking) and adapt them to Chefs specific food manipulation challenges
Work with the platform team to build data collection pipelines using teleoperation kinesthetic teaching and autonomous rollouts; work with the data team on dataset curation augmentation and training infrastructure
Define evaluation metrics and regression benchmarks that accurately predict real-world manipulation performance; build recovery and fallback behaviors that handle dropped items mis-grasps and partial occlusions gracefully
Partner with perception and robotics engineers to validate end-to-end grasp-to-place performance across new food classes and end effector configurations
What You Bring:
MS or PhD in Robotics Machine Learning Computer Science or a closely related field or equivalent practical experience
5 years of experience developing and deploying ML systems for robotics manipulation visuomotor control or robot learning
Deep expertise in at least two of: imitation learning reinforcement learning grasp estimation or learned motion generation
Strong PyTorch skills and experience building reliable production-quality training and evaluation pipelines
Hands-on experience deploying policies to real robotic hardware not just simulation results
Strong software engineering fundamentals in Python; ability to write maintainable well-tested code across research and production codebases
Track record of owning projects end-to-end: from problem framing through field deployment and iteration
Nice-to-have:
Experience with Vision-Language-Action (VLA) models diffusion policies or transformer-based action representations
Familiarity with simulation environments (MuJoCo Isaac Sim Genesis) and sim-to-real transfer techniques
Experience with multiple end effector types suction parallel jaw multi-finger or soft grippers
Background in food agriculture or consumer goods robotics where object variability is high
Experience with model compression quantization or TensorRT for edge deployment
Contributions to open robotics datasets or publications at CoRL ICRA RSS NeurIPS or similar venues
Experience using simulation environments (e.g. Isaac Sim Gazebo) for synthetic data generation and domain randomization
$200000 - $300000 a year
Chef is an early-stage startup where equity is a major part of the compensation package. Our salary ranges are determined by role level and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position. Within the range individual pay is determined by additional factors including job-related skills experience and relevant education or training.
In addition to salary and early-stage equity we offer a comprehensive benefits package that includes medical dental and vision insurance commuter benefits flexible paid time off (PTO) catered lunch and 401(k) matching.
Chef Robotics is solving one of the hardest problems in AI and robotics and we ship. Our robots are in production today generating real data that trains the next generation of food AI. Backed by Kleiner Perkins Construct Bloomberg Beta and Promus Ventures and built by a team from Cruise Zoox Google Tesla and Amazon Robotics were scaling fast with multiple multi-year enterprise contracts. If you want to build physical AI with real-world deployments and real impact Chef is the place.
We may use artificial intelligence (AI) tools to support parts of the hiring process such as reviewing applications analyzing resumes or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed please contact us.
Required Experience:
Senior IC
Chef Robotics is accelerating the deployment of intelligent machines in the physical world starting with food production the sector facing the largest labor shortage in the U.S. with 1.14M unfilled jobs today and 3.1M projected by 2030. These roles cant be offshored making robotics essential to kee...
Chef Robotics is accelerating the deployment of intelligent machines in the physical world starting with food production the sector facing the largest labor shortage in the U.S. with 1.14M unfilled jobs today and 3.1M projected by 2030. These roles cant be offshored making robotics essential to keeping production onshore and strengthening Americas manufacturing base.
Our AI-powered robots automate food prep and assembly in commercial kitchens and food manufacturing and have already produced over 110 million meals in production generating the worlds largest proprietary dataset for deformable food manipulation. Backed by investors including Kleiner Perkins Construct Bloomberg Beta and Promus Ventures and built by a team from Cruise Zoox Google Tesla and Amazon Robotics Chef is rapidly scaling with multiple multi-year contracts and a mission to put an intelligent robot in every commercial kitchen.
About the Role
Chef Robotics is building autonomous robots that work alongside humans in commercial food preparation environments. Manipulation is one of the hardest open problems in robotics and food makes it harder. Unlike structured industrial parts food items are deformable visually similar irregularly shaped and behave differently depending on temperature moisture and preparation state. At Chef were solving this in production every day across a growing menu of meal types and preparation configurations.
As a Senior ML Engineer Manipulation you will own the learning systems that enable our robots to reliably pick place and handle diverse food classes using multiple end effectors from suction grippers to multi-finger hands. You will work end-to-end: from defining data collection strategies and training policies to deploying and debugging those policies on physical robots in real environments.
We are a small high-ownership team. We work onsite five days a week and move with startup urgency.
In this role you will:
Design and train manipulation policies behavior cloning imitation learning and RL for dexterous food handling across diverse item classes and end effector types (suction parallel jaw multi-finger)
Implement and evaluate modern policy architectures (diffusion policies transformer-based action models action chunking) and adapt them to Chefs specific food manipulation challenges
Work with the platform team to build data collection pipelines using teleoperation kinesthetic teaching and autonomous rollouts; work with the data team on dataset curation augmentation and training infrastructure
Define evaluation metrics and regression benchmarks that accurately predict real-world manipulation performance; build recovery and fallback behaviors that handle dropped items mis-grasps and partial occlusions gracefully
Partner with perception and robotics engineers to validate end-to-end grasp-to-place performance across new food classes and end effector configurations
What You Bring:
MS or PhD in Robotics Machine Learning Computer Science or a closely related field or equivalent practical experience
5 years of experience developing and deploying ML systems for robotics manipulation visuomotor control or robot learning
Deep expertise in at least two of: imitation learning reinforcement learning grasp estimation or learned motion generation
Strong PyTorch skills and experience building reliable production-quality training and evaluation pipelines
Hands-on experience deploying policies to real robotic hardware not just simulation results
Strong software engineering fundamentals in Python; ability to write maintainable well-tested code across research and production codebases
Track record of owning projects end-to-end: from problem framing through field deployment and iteration
Nice-to-have:
Experience with Vision-Language-Action (VLA) models diffusion policies or transformer-based action representations
Familiarity with simulation environments (MuJoCo Isaac Sim Genesis) and sim-to-real transfer techniques
Experience with multiple end effector types suction parallel jaw multi-finger or soft grippers
Background in food agriculture or consumer goods robotics where object variability is high
Experience with model compression quantization or TensorRT for edge deployment
Contributions to open robotics datasets or publications at CoRL ICRA RSS NeurIPS or similar venues
Experience using simulation environments (e.g. Isaac Sim Gazebo) for synthetic data generation and domain randomization
$200000 - $300000 a year
Chef is an early-stage startup where equity is a major part of the compensation package. Our salary ranges are determined by role level and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position. Within the range individual pay is determined by additional factors including job-related skills experience and relevant education or training.
In addition to salary and early-stage equity we offer a comprehensive benefits package that includes medical dental and vision insurance commuter benefits flexible paid time off (PTO) catered lunch and 401(k) matching.
Chef Robotics is solving one of the hardest problems in AI and robotics and we ship. Our robots are in production today generating real data that trains the next generation of food AI. Backed by Kleiner Perkins Construct Bloomberg Beta and Promus Ventures and built by a team from Cruise Zoox Google Tesla and Amazon Robotics were scaling fast with multiple multi-year enterprise contracts. If you want to build physical AI with real-world deployments and real impact Chef is the place.
We may use artificial intelligence (AI) tools to support parts of the hiring process such as reviewing applications analyzing resumes or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed please contact us.
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