SI Engineer - Computer Use Agents, Digital Optimus

Job Description

Job Responsibilities

• Design and implement novel SI 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 SI for practical applications
• Ensure our systems are steerable and interpretable

Job 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