Machine Learning Engineer, Network Deployment & Inference, Optimus

Machine Learning Engineer, Network Deployment & Inference, OptimusJoin to apply for the Machine Learning Engineer, Network Deployment & Inference, Optimus role at TeslaMachine Learning Engineer, Network Deployment & Inference, OptimusJoin to apply for the Machine Learning Engineer, Network Deployment & Inference, Optimus role at TeslaGet AI-powered advice on this job and more exclusive features.What To ExpectTesla is building robust, real-world AI through humanoid robots. As a Software Engineer within our robotics teams, you will contribute to one of the most advanced Robotics/AI Platforms in the world. You’ll be responsible for integrating machine learning models with real-time systems, working across the software stack to ensure seamless communication between neural networks and hardware components.This role is ideal for engineers with strong systems-level & networking expertise, and a solid grasp of machine learning principles—especially those excited by the challenge of deploying AI into the real world. Your work can cover everything from tuning the robot's whole-body control stack to building the infrastructure that will scale the entire robot fleet. You will help implement innovative features that leverage the power of Tesla AI. You will define and maintain content and configurations that support smooth functionality across variations of the robot platform.What You'll DoDesign and implement efficient, robust C++ systems for real-time ML inference and control and for the humanoid robot software stackIntegrate ML models into embedded or robotic systems with tight latency and performance constraintsWrite Python scripts/tools for training, evaluation, and deployment pipelinesCollaborate with machine learning researchers to bring models from prototype to productionOptimize runtime performance of neural networks on various compute environments (e.g., GPU, CPU, edge accelerators)Work with sensors and actuatorsDevelop messaging frameworks (e.g., ROS, ZeroMQ, gRPC)What You'll BringPractical experience programming in C/C++ software, including modern C/C++ (C++14/17/20), multithreading, and PythonSolid understanding of machine learning fundamentals (e.g., supervised learning, neural networks, model evaluation)Experience with model inference, deployment, and optimizationExperience with embedded systems software design conceptsExperience with communication standards such as CAN, ethercat and ethernetProficient developing software on a Linux host, for embedded Linux targets (cross-compilation, etc.) is a plusExcellent problem solving, critical thinking, and communication skillsBenefitsCompensation and BenefitsAlong with competitive pay, as a full-time Tesla employee, you are eligible for the following benefits at day 1 of hire:Aetna PPO and HSA plans > 2 medical plan options with $0 payroll deductionFamily-building, fertility, adoption and surrogacy benefitsDental (including orthodontic coverage) and vision plans, both have options with a $0 paycheck contributionCompany Paid (Health Savings Account) HSA Contribution when enrolled in the High Deductible Aetna medical plan with HSAHealthcare and Dependent Care Flexible Spending Accounts (FSA)401(k) with employer match, Employee Stock Purchase Plans, and other financial benefitsCompany paid Basic Life, AD&D, short-term and long-term disability insuranceEmployee Assistance ProgramSick and Vacation time (Flex time for salary positions), and Paid HolidaysBack-up childcare and parenting support resourcesVoluntary benefits to include: critical illness, hospital indemnity, accident insurance, theft & legal services, and pet insuranceWeight Loss and Tobacco Cessation ProgramsTesla Babies programCommuter benefitsEmployee discounts and perks programExpected Compensation$140,000 - $420,000/annual salary + cash and stock awards + benefitsPay 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., TeslaSeniority levelSeniority levelEntry levelEmployment typeEmployment typeFull-timeJob functionJob functionEngineering and Information TechnologyIndustriesMotor Vehicle Manufacturing, Renewable Energy Semiconductor Manufacturing, and UtilitiesReferrals increase your chances of interviewing at Tesla by 2xGet notified about new Machine Learning Engineer jobs in Palo Alto, CA.AI/ML Engineer (Multiple roles and seniority levels)San Jose, CA $137,500.00-$236,500.00 4 days agoSan Jose, CA $120,700.00-$228,600.00 5 days agoMilpitas, CA $152,500.00-$219,200.00 2 weeks agoSan Jose, CA $120,700.00-$228,600.00 5 days agoMachine Learning Engineer (I, II, or Sr.)New Grads 2025 - Software Engineer - Computer Vision/Deep LearningSan Jose, CA $120,000.00-$165,000.00 9 months agoNew Grads 2025 - Software Engineer, AlgorithmSan Jose, CA $120,000.00-$165,000.00 10 months agoSan Jose, CA $120,700.00-$228,600.00 4 days agoMachine Learning Engineer (I, II, or Sr.)Sunnyvale, CA $158,200.00-$185,000.00 3 weeks agoSan Jose, CA $137,500.00-$236,500.00 1 month agoSoftware Engineer, AI Platform - New GradMountain View, CA $145,000.00-$170,000.00 2 days agoMachine Learning Engineer, Early Stage ProjectMountain View, CA $136,000.00-$185,000.00 1 week agoSan Jose, CA $120,700.00-$228,600.00 5 days agoSunnyvale, CA $167,000.00-$185,500.00 2 weeks agoSunnyvale, CA $167,000.00-$185,500.00 1 month agoSan Jose, CA $118,657.00-$187,200.00 1 week agoSan Jose, CA $120,000.00-$240,000.00 4 months agoSan Jose, CA $169,500.00-$291,500.00 4 days agoSan Jose, CA $120,700.00-$301,200.00 5 days agoNew Grads 2025 - General Software EngineerSan Jose, CA $120,000.00-$165,000.00 6 months agoSan Jose, CA $142,700.00-$257,600.00 5 days agoRedwood City, CA $167,200.00-$250,800.00 1 week agoSan Jose, CA $130,000.00-$182,000.00 11 months agoWe’re unlocking community knowledge in a new way. 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