Machine Learning: Multimodal Foundation Models

The Bot Company

• We're building a helpful robot for every home.
• We're a small team of engineers, designers, and operators based in San Francisco.
• Our team comes from Tesla, Cruise, OpenAI, Google, Pixar, and many other great companies.
• In the past we've shipped to hundreds of millions of users and know what it takes to build amazing products and experiences.
• Our team is deliberately lean to promote rapid decision making and do away with bureaucracy and hierarchy.
• Everyone is an IC and is empowered with massive scope, radical ownership, and direct responsibility.
• We work across the stack with a culture built for rapid iteration and fast execution.
• What we look for in all candidates All roles at The Bot Company demand extreme sharpness and the ability to move fast in high-intensity environments.
• Throughout the process, we expect candidates to demonstrate: Exceptional mental acuity: you think quickly, learn instantly, and reason across unfamiliar domains.
• Engineering curiosity: you naturally dig into how systems work, even outside your specialty.
• High performance mindset: you move fast, handle ambiguity, and excel when the environment is demanding.
• Machine Learning: Multimodal Foundation Models We are building unified foundation models that natively reason across text, image, video, and kinematics to drive intelligent robotic policies.
• You will work on large multi-modal networks and own the entire stack from data to training and deploying models.

What You'll Do

Build Native Multimodal Policies: Develop architectures where vision, language, and more modalities share a unified representation. Improve Cross-Modal Reasoning: Research and implement methods to ensure the model doesn't just "associate" modalities but actually reasons through them (e.g., grounding visual physics in kinematic constraints). Own the Training Loop End-to-End: Design, run, debug, and iterate on large-scale training experiments; diagnosing failure modes, improving data mixtures, and tightening evaluation to drive measurable gains. Ship and Iterate on Real Systems: Integrate models into real robotic stacks, build on robot code to deploy your models, and optimize performance for edge inference.

Requirements

• Very strong coding skills in Python, C++, or Rust.
• Production MLLM Experience: Track record of training and deploying large-scale multimodal models.
• Pretraining & RL Mastery: Deep intuition for LLM-style pretraining, post-training, and Reinforcement Learning at scale.
• Infrastructure Fluency: Comfortable managing and optimizing large-scale experiments on massive GPU clusters.
• Why Join You’ll work with a small, elite team on challenges that require speed, intelligence, and deep engineering instinct.
• If you enjoy understanding systems at all levels, move fast, and think even faster, you’ll thrive here.