Machine Learning Engineer, Model Optimization & Deployment, Optimus

What to Expect

Tesla is building robust, real-world AI through humanoid robots. As a Software Engineer for the Optimus team, you will build the tools and infrastructure to make and measure improvements to neural network architecture, visualize data, assist with exporting and deploying neural networks to Tesla's neural network chip with real-time latency constraints on Optimus, and evaluate experimental results. You will help us automate the entire workflows of training, validation, and production of Optimus. Most importantly, you will see your work repeatedly shipped to and utilized by thousands of Humanoid Robots in real world applications.

What You'll Do

• Optimize ML models for latency, memory usage, and inference speed
• Quantize, prune, and convert models (e.g., to ONNX, TensorRT, TFLite) for deployment on various platforms (cloud, edge, mobile)
• Benchmark and profile model performance across different environments
• Package and deploy models as REST APIs, batch jobs, or streaming services using tools like FastAPI, Flask, or gRPC
• Implement CI / CD pipelines for automated testing and deployment of ML models
• Ensure scalability and reliability of ML services in production environments

What You'll Bring

Compensation and Benefits

Along with competitive pay, as a full-time Tesla employee, you are eligible for the following benefits at day 1 of hire :

2 medical plan options with $0 payroll deduction

Expected Compensation : $140,000 - $420,000 / annual salary + cash and stock awards + benefits. Pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience.

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