Machine Learning Engineer, Digital Optimus - Palo Alto [272309]

$124,000 - $420,000 yearly

Job Description

As a Machine Learning Engineer at Tesla AI working on Digital Optimus, you will build training, inference, data, and evaluation systems for frontier computer-use agents. These agents combine high-level reasoning models with real-time vision to ingest computer screen video, understand UIs, execute actions, and complete complex digital workflows autonomously.

We are looking for ML generalists or domain specialists with strong applied ML fundamentals who excel at turning research ideas into reliable production systems.

The Role

  • Build training pipelines that turn real agent interactions (screen data, actions, outcomes) into model improvements
  • Design model architecture and training recipes to improve performance in a scientific way.
  • Design evaluation frameworks and benchmarks to measure agent performance and identify failure modes
  • Create data systems that extract high-quality signals from agent runs for continuous iteration
  • Develop inference and model routing logic to combine reasoning and vision models efficiently in real time
  • Ship end-to-end improvements that increase agent reliability and autonomy on long-horizon tasks

Requirements

  • Strong applied ML fundamentals with a passion for turning research into robust, production-grade systems
  • Experience designing model architectures and/or building training workflows, evaluation tools, data pipelines, or inference optimizations
  • Solid software engineering skills and a high sense of ownership
  • Background in agentic systems and/or multimodal (vision + language) models
  • Excitement about making multimodal models reliable and effective in real-world agentic environments
  • Experience with post-training or RL methods (PPO, GRPO, RLHF) is a strong plus
Anthony Antonucci

Qualifications

Relevant experience in Tesla AI; strong problem-solving skills; commitment to Tesla mission.

Immediate Fill

No