Chef Robotics is on a mission to accelerate the advent of intelligent machines in the physical world. As the rise of LLMs like ChatGPT has shown AI has the potential to drive immense change. However we believe AIs biggest impact will be in the physical world given industries like manufacturing food and transportation represent 90% of global GDP. Were starting with food with a goal to put an intelligent robot in every commercial kitchen in the world. We have signed multiple multi-year contracts with various large food companies and we are growing fast. Were backed by investors like Kleiner Perkins Construct Bloomberg BETA and Promus Ventures. We have a great team where you will be surrounded by talented engineers and tech leaders from companies like Cruise Zoox Google Verb Surgical Tesla Nuro Vicarious Amazon Robotics Strateos Built Robotics Facebook Plenty Yelp and Microsoft.
About the Role
As an Applied ML Research Engineer youll design and implement cutting-edge reinforcement learning and imitation learning systems for robotic food manipulation. Youll build RL/IL algorithms that solve real production challenges - from adaptive manipulation across thousands of ingredient types to multi-arm coordination - and deploy them in commercial environments serving millions of meals.
What Youll Do:
Build and deploy RL/IL systems for robotic food manipulation developing policies that adapt to diverse ingredients with minimal human intervention
Engineer multi-agent RL solutions for dual-arm coordination and collaborative manipulation workflows in high-throughput environments
Implement imitation learning pipelines to rapidly onboard new ingredients from minimal demonstrations reducing manual tuning
Integrate research prototypes into production systems working closely with robotics software engineers on real-world deployment
Minimum Qualifications
MS/PhD in Computer Science Robotics or related field OR Bachelors 7 years industry experience5 years hands-on experience implementing RL/IL algorithms for robotics applications
Expert knowledge building and deploying RL systems (policy gradients actor-critic model-based RL) and IL methods (behavioral cloning inverse RL)
Strong software engineering skills with ML frameworks (PyTorch TensorFlow) Python and robotics frameworks (ROS)
Preferred Qualifications
Publications at top robotics/AI conferences on RL/IL implementations (ICRA IROS RSS CoRL NeurIPS ICML)
Experience building multi-agent RL hierarchical RL or meta-learning systems for robotics
Hands-on experience with sim-to-real transfer domain adaptation and sample-efficient learning for manipulation
Background implementing RL/IL for manufacturing automation contact-rich manipulation or similar domains
Strong systems engineering skills and experience with distributed training and inference
$150000 - $260000 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.
Equal Opportunity Employer
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race religion color sex gender identity and expression sexual orientation national origin ancestry citizen status uniform service member and veteran status marital status age pregnancy status protected medical condition genetic information disability or any other protected status.
Multiple studies have found that a higher percentage of women and BIPOC candidates wont apply if they dont meet every listed qualification. Chef values candidates of all backgrounds. If you find yourself excited by our mission but you dont check every box in the description we encourage you to apply anyway!
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