Senior ML Engineer, Foundation Models
Job Location:
San Francisco, CA - USA
Yearly Salary:
Posted:
Application Deadline:
Vacancies:
Job Summary
Chef Robotics is bringing AI into the physical world starting with one of the worlds largest industries: food manufacturing.
Food production faces one of the most severe labor shortages in the US with more than 1 million open jobs today and demand continuing to grow. Our robots help manufacturers automate repetitive food-preparation and assembly tasks so they can increase throughput improve consistency and keep production onshore.
Today Chef robots operate in production facilities across North America and Europe serving customers including Amys Kitchen gategroup and CookUnity. Our robots have made over 100 million servings in production creating the worlds largest proprietary dataset for AI-powered manipulation of deformable food. Every meal our robots produce makes the system smarter.
Backed by leading investors including Avataar Ventures Construct Capital Bloomberg Beta Promus Ventures and Kleiner Perkins were scaling rapidly with a robotics-as-a-service (RaaS) model and long-term customer partnerships. Our team includes engineers and leaders from Google Cruise Tesla Amazon Robotics Dexterity Bear Robotics Saildrone and Zoox united by a mission to build intelligent machines that solve meaningful problems in the real world.
If youre excited about solving hard problems creating real customer impact and shipping systems that operate in production every day not just in the lab youll feel at home at Chef.
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.
- 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
- 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
- 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
- Experience deploying models to edge hardware (ONNX TensorRT quantization performance profiling)
- Prior work with contact-rich manipulation deformable object handling or food robotics
- Publications at top venues: CoRL RSS ICRA NeurIPS ICML ICLR
Chef Robotics is solving one of the hardest problems in AI: bringing intelligence into the physical world.
Our robots are already operating in production facilities every day generating the real-world data that powers the next generation of embodied AI. If you want to build technology that leaves the lab ships to customers and transforms an industry Chef is the place to do it.
Required Experience:
Senior IC
