AI Engineer, Computer Use Agents, Digital Optimus

As an AI Engineer on the Computer Use Agents team, you will develop AI agents to interact with computer interfaces and perform long-horizon agentic behaviors. Our approach to agentic computer use is modeled after real-time control policies, rather than screenshot-based VLM agents, with the larger goal of integrating with Tesla's broader AI ecosystem for autonomy and robotics. Top candidates will have both an understanding of standard VLM-based approaches to computer use as well as real-time control policies for robotics. You will join a small group of world-class deep learning experts to develop novel architectures and push the boundaries of AI research and development.

Responsibilities

Design and implement novel AI agents for computer use, using imitation and reinforcement learning to enable tasks like autonomous software interaction, code generation, and real-time decision-making Build and optimize scalable training environments for agentic models, focusing on ultra-realistic settings that test ambiguity, interruptions, and long-horizon context retention Architect models that are optimized for our edge device deployment, co-designing for our hardware constraints Apply reinforcement learning techniques, both online and offline, to refine and boost agent performance Design architectures that perform efficient context management and reasoning for long-horizon agentic planning tasks Develop rigorous benchmarks and techniques to evaluate agent performance Collaborate across research, infrastructure, and production teams to integrate agent systems into Tesla's autonomy and robotics platforms, such as Full Self-Driving (FSD) and Optimus Iterate rapidly on prototypes, debug complex ML stacks, and contribute to research directions that advance agentic AI for practical applications Ensure our systems are steerable and interpretable

Requirements

2-4 years of experience in machine learning, reinforcement learning, or large language model training/fine-tuning Proficiency in Python and a deep understanding of software engineering best practices Proficiency in deep learning frameworks such as PyTorch, JAX, or TensorFlow Strong problem-solving skills and ability to work effectively in cross-functional teams Strong work ethic and willingness to take on multiple roles