Machine Learning: Multimodal Foundation Models

The Bot Company

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San Francisco Until 8/21/2026 First posted March 18, 2026 Last posted March 18, 2026
Job description

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.

Compensation (from employer):
Base $200K – $350K

About this role

Summary

Develop and deploy large-scale multimodal models for robotics applications.

Job title

Machine Learning: Multimodal Foundation Models

Experience level

production ml modeling experience

Industry

software

Location requirements

San Francisco with remote work possible

Salary

Base $200K – $350K

Management role

No

Skills & keywords

Required skills

PythonC++production mllarge-scale traininginfrastructure

Preferred skills

Rustreinforcement learningdistributed training

Specializations

multimodal modelscross-modal reasoningrobotics
Locations

Structured locations inferred from the posting.

San Francisco, CA, USA

Hybrid City