About the job
The Bot Company
At The Bot Company, we are on a mission to create an innovative robot designed for every household.
Our dynamic team, comprised of talented engineers, designers, and operators, is based in San Francisco. With backgrounds from industry leaders like Tesla, Cruise, OpenAI, Google, and Pixar, we have a proven track record of delivering exceptional products to millions of users.
We embrace a lean structure that fosters quick decision-making and eliminates unnecessary bureaucracy. Every team member is an individual contributor (IC) with significant autonomy, radical ownership, and direct accountability. Our culture promotes collaboration across the stack, emphasizing rapid iteration and fast execution.
Candidate Profile
We seek candidates who exhibit outstanding sharpness and thrive in fast-paced, high-pressure environments. Throughout the hiring process, you should demonstrate:
Exceptional Mental Acuity: An ability to think quickly, learn rapidly, and reason effectively across diverse domains.
Engineering Curiosity: A natural inclination to explore and understand how systems function, even outside your area of expertise.
High Performance Mindset: A capacity to act swiftly, navigate ambiguity, and excel in demanding environments.
Role Overview: Machine Learning - Whole-Body Control
You will be instrumental in developing high-performance whole-body controllers that deliver agile motion and manipulation capabilities in real-world settings.
Your responsibilities will include training low-level control policies in simulation and overseeing the entire stack, from environment design to large-scale training and simulation-to-real deployment.
Your Responsibilities
Train whole-body policies for locomotion, manipulation, and coordinated movements.
Develop scalable simulation environments using IsaacLab, MuJoCo, or similar tools, incorporating parallel rollouts.
Create reward systems and educational curricula that support stable long-horizon learning.
Take ownership of sim-to-real transfer through domain randomization and structured evaluations.
Execute and troubleshoot large-scale GPU training experiments.
Qualifications
Proficiency in programming languages such as Python, C++, or Rust; knowledge of CUDA is advantageous.
Solid understanding of contemporary reinforcement learning principles.
Experience in building and deploying machine learning models in real-world applications.