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
The next leap in food robotics wont come from hand-tuned policies for individual ingredients it will come from foundation models that generalize across thousands of food types kitchen configurations and manipulation scenarios out of the box. At Chef were building that model: the Food Foundation Model.
As a Senior ML Engineer Foundation Models you will work at the frontier of large-scale robot learning: training and fine-tuning the Food Foundation Model building the data infrastructure that feeds it and deploying it onto physical robots in production kitchens. Youll bridge research and engineering translating advances from the latest policy learning generative modeling and world model literature into systems that handle real food with real end effectors at real throughput. Your models wont just benchmark well; theyll serve millions of meals.
We are a small high-ownership team. We work onsite five days a week and move with startup urgency.
In this role you will:
Define the architecture training objectives and learning approach for the Food Foundation Model evaluating tradeoffs across generalization sample efficiency and deployment constraints
Investigate and evaluate the latest foundation model architectures including VLAs world models JEPA-style joint embedding models diffusion policies and emerging approaches and assess their applicability to Chefs manipulation and generalization challenges
Design pre-training fine-tuning and alignment pipelines that improve the models ability to generalize across new food types kitchen configurations and end effector types with minimal retraining
Develop evaluation frameworks that measure real-world generalization and long-horizon reliability not just offline benchmark accuracy
Collaborate with the data and platform teams on training data requirements augmentation strategies and model serving constraints
Stay current with the research frontier reading and critically evaluating recent work from CoRL RSS NeurIPS ICML and ICLR and forming clear views on whats relevant to production manipulation
What You Bring:
MS or PhD in Machine Learning Robotics Computer Science or a related field or equivalent industry experience
5 years of experience implementing and deploying ML models for real-world robotics applications
Hands-on experience with large-scale model training: pre-training fine-tuning and post-training alignment pipelines
Familiarity with modern policy and generative model architectures diffusion models transformers behavior cloning or large-scale multimodal models
Strong PyTorch skills and experience building reliable production-quality training and evaluation infrastructure
Solid software engineering fundamentals in Python; able to write maintainable code across research and production codebases
Track record of taking models from research prototype to deployed system on physical hardware
Nice-to-have:
Experience with world models or generative models for robot planning and prediction
Background in large-scale distributed training (multi-node GPU clusters FSDP DeepSpeed)
Familiarity with simulation environments (MuJoCo Isaac Sim Genesis) for synthetic data generation and domain randomization
Prior work with contact-rich manipulation deformable object handling or food robotics
Publications at top venues: CoRL RSS ICRA NeurIPS ICML ICLR
$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
The next leap in food robotics wont come from hand-tuned policies for individual ingredients it will come from foundation models that generalize across thousands of food types kitchen configurations and manipulation scenarios out of the box. At Chef were building that model: the Food Foundation Model.
As a Senior ML Engineer Foundation Models you will work at the frontier of large-scale robot learning: training and fine-tuning the Food Foundation Model building the data infrastructure that feeds it and deploying it onto physical robots in production kitchens. Youll bridge research and engineering translating advances from the latest policy learning generative modeling and world model literature into systems that handle real food with real end effectors at real throughput. Your models wont just benchmark well; theyll serve millions of meals.
We are a small high-ownership team. We work onsite five days a week and move with startup urgency.
In this role you will:
Define the architecture training objectives and learning approach for the Food Foundation Model evaluating tradeoffs across generalization sample efficiency and deployment constraints
Investigate and evaluate the latest foundation model architectures including VLAs world models JEPA-style joint embedding models diffusion policies and emerging approaches and assess their applicability to Chefs manipulation and generalization challenges
Design pre-training fine-tuning and alignment pipelines that improve the models ability to generalize across new food types kitchen configurations and end effector types with minimal retraining
Develop evaluation frameworks that measure real-world generalization and long-horizon reliability not just offline benchmark accuracy
Collaborate with the data and platform teams on training data requirements augmentation strategies and model serving constraints
Stay current with the research frontier reading and critically evaluating recent work from CoRL RSS NeurIPS ICML and ICLR and forming clear views on whats relevant to production manipulation
What You Bring:
MS or PhD in Machine Learning Robotics Computer Science or a related field or equivalent industry experience
5 years of experience implementing and deploying ML models for real-world robotics applications
Hands-on experience with large-scale model training: pre-training fine-tuning and post-training alignment pipelines
Familiarity with modern policy and generative model architectures diffusion models transformers behavior cloning or large-scale multimodal models
Strong PyTorch skills and experience building reliable production-quality training and evaluation infrastructure
Solid software engineering fundamentals in Python; able to write maintainable code across research and production codebases
Track record of taking models from research prototype to deployed system on physical hardware
Nice-to-have:
Experience with world models or generative models for robot planning and prediction
Background in large-scale distributed training (multi-node GPU clusters FSDP DeepSpeed)
Familiarity with simulation environments (MuJoCo Isaac Sim Genesis) for synthetic data generation and domain randomization
Prior work with contact-rich manipulation deformable object handling or food robotics
Publications at top venues: CoRL RSS ICRA NeurIPS ICML ICLR
$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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