AI Infrastructure Engineer, Model Optimization & Deployment, Optimus

Tesla Motors
Palo Alto, CA, United States
about 2 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Compensation
$176,000.0
Working hours
Regular working hours

Tech stack

Artificial Intelligence Amazon Web Services Artificial Neural Networks Automation of Tests Microsoft Azure Cloud Computing Program Optimization Serialization Memory Management Protocol Buffers Python (Programming Language) Machine Learning
+19 more
Prometheus Azure Machine Learning Smart Devices Software Engineering AI Infrastructure Google Cloud Pytorch Flask (Web Framework) Grafana Fastapi Containerization Kubernetes ONNX (Open Neural Network Exchange) Format Avro Machine Learning Operations TensorRT Restful APIs Serverless Computing Docker

Job description

Tesla AIissolvingrobust, 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,assistwith exporting and deploying neural networks toTesla’sneural 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 ofOptimus. Most importantly, you will see your work repeatedly shipped to andutilizedby 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

Requirements

  • 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 & conditions

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

  • Medical plans > plan options with $0 payroll deduction
  • Family-building, fertility, adoption and surrogacy benefits
  • Dental (including orthodontic coverage) and vision plans, both have options with a $0 paycheck contribution
  • Company Paid (Health Savings Accounts) HSA Contribution when enrolled in the High-Deductible medical plan with HSA
  • Healthcare and Dependent Care Flexible Spending Accounts (FSA)
  • 401(k) with employer match, Employee Stock Purchase Plans, and other financial benefits
  • Company paid Basic Life, AD&D
  • Short-term and long-term disability insurance (90 day waiting period)
  • Employee Assistance Program
  • Sick and Vacation time (Flex time for salary positions, Accrued hours for Hourly positions), and Paid Holidays
  • Back-up childcare and parenting support resources
  • Voluntary benefits to include: critical illness, hospital indemnity, accident insurance, theft & legal services, and pet insurance
  • Weight Loss and Tobacco Cessation Programs
  • Tesla Babies program
  • Commuter benefits
  • Employee discounts and perks program

Expected Compensation $176,000 - $420,000/annual salary + cash and stock awards + benefits

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on diversityjobs.com

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

2:15 min

Open-source community and machine learning frameworks

Gian Marco Iodice Gian Marco Iodice · WWC 2025

3:33 min

Connecting frontends via a FastAPI proxy backend layer

Saoussen Chaabnia Saoussen Chaabnia · Europe 2026 Virtual

2:07 min

Inspecting default bridge architectures and custom Docker networks

Oliver Seitz Oliver Seitz · WWC 2025

3:02 min

Audience Q&A on data formats and engine tradeoffs

Matthias Niehoff Matthias Niehoff · WWC Europe 2026

1:42 min

Introduction to the fast API web framework

Sebastián Ramírez · WWC 2022

2:34 min

Docker sandbox architecture and microVM environment integration

Manuel de la Peña Manuel de la Peña · WWC Europe 2026

Videos

See all

Related articles

See all