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 DoOptimize 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
Strong proficiency in Python and PyTorch
Experience with model optimization tools (e.g., ONNX, TensorRT , TFLite , TVM)
Experience with model inference optimization and quantization
Solid understanding of containerization and orchestration (Docker, Kubernetes)
Familiarity with cloud platforms (AWS, GCP, Azure) and serverless deployments
Strong grasp of software engineering principles and CI/CD pipelines
Experience deploying models to edge devices or mobile platforms
Knowledge of data serialization formats (e.g., protobuf , Avro)
Exposure to observability tools (e.g., Prometheus, Grafana) for ML monitoring
Benefits
Along with competitive pay, as a full-time Tesla employee, you are eligible for the following benefits at day 1 of hire:
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. The total compensation package for this position may also include other elements dependent on the position offered. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.
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