Senior Perception Engineer

Chef Robotics is bringing AI into the physical world, starting with one of the world’s 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 Amy’s Kitchen, gategroup, and CookUnity. Our robots have made over 100 million servings in production, creating the world’s 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, we’re 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 you’re excited about solving hard problems, creating real customer impact, and shipping systems that operate in production every day, not just in the lab, you’ll feel at home at Chef.

About the Role
Chef Robotics is building autonomous robots that work alongside humans in commercial food preparation environments - and perception is at the heart of what makes them reliable. As a Perception Engineer, you will own the full stack of how our robots see and understand the world: from integrating cutting-edge camera hardware, to training production-grade deep learning models, to ensuring those models perform accurately and efficiently in real-time on the factory floor. You will work on some of the most technically rich problems in applied robotics - dense instance segmentation of deformable food items, real-time inference under tight latency constraints, sensor fusion, and robust tracking in cluttered, dynamic environments. You will not just train models; you will design the pipelines that gather and curate data, define the architectures that balance accuracy and speed, and own the deployment and field troubleshooting of what you build. We are a small, high-ownership team. We work onsite five days a week and move with startup urgency - you will be expected to go deep technically while staying pragmatic about what ships.

In this role, you will:

• Design, train, and optimize deep learning models for detection, segmentation, segmentation, pose estimation, and classification - with a focus on real-world robustness over benchmark performance.
• Build low-latency inference pipelines that approach real-time performance; profile and optimize models for deployment on embedded and edge hardware.
• Develop and improve multi-object tracking algorithms for reliable identification and motion prediction of items across frames.
• Solve challenging perception problems specific to food robotics: deformable objects, occlusions, varying lighting, and high visual similarity between categories.
• Own the end-to-end ML lifecycle: data collection strategy, annotation tooling, dataset curation, augmentation pipelines, model training, evaluation, deployment, and field debugging.
• Develop tooling to monitor model performance in production and drive continuous improvement cycles.
• Partner closely with robotics, hardware, and software engineers to translate perception capabilities into reliable end-to-end robot behaviors.
• Help define the perception roadmap and influence technical direction as the team grows.
• Assist in integrating new cameras and sensors for enhanced robotic vision.

What You Bring:

• BS, MS, or PhD in Computer Science, Robotics, Electrical Engineering, or a closely related field.
• 5+ years of combined research and industry experience in computer vision and machine learning, with a track record of shipping perception systems to production.
• Deep expertise in at least two of: instance/semantic segmentation, object detection, 3D perception, or multi-object tracking.
• Strong Python skills; experience building production-quality, maintainable code - not just research prototypes.
• Hands-on experience with deep learning frameworks (PyTorch strongly preferred) and the full training pipeline from data to deployed model.
• Experience working with RGBD sensors, depth cameras, and point cloud data.
• Proven ability to build and optimize models for low-latency, real-time inference.
• Familiarity with ROS or similar robotics middleware.

Nice-to-have:

• Experience using simulation environments (e.g. Isaac Sim, Gazebo) for synthetic data generation, domain randomization, and sim-to-real transfer of perception models.
• C++ proficiency for performance-critical modules and embedded deployment.
• Experience with cloud ML infrastructure (GCP, AWS) and containerization (Docker, Kubernetes).
• Background in autonomous vehicles, warehouse robotics, or other perception-heavy robotics applications.
• Contributions to open-source CV/ML projects or publications in top-tier venues (CVPR, ECCV, NeurIPS, etc.).

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.