Tesla
Machine Learning Systems Engineer, Tooling & Infrastructure, Optimus
Tesla, Palo Alto, California, United States, 94306
Machine Learning Systems Engineer, Tooling & Infrastructure, Optimus
Join to apply for the Machine Learning Systems Engineer, Tooling & Infrastructure, Optimus role at Tesla. Get AI-powered advice on this job and more exclusive features. What To Expect
As a Software Engineer for the Optimus team, you will build the tools and infrastructure to make and measure improvements to neural network architecture by building and automating scalable data and inference pipelines, ensuring data quality by building visualizing tools. We are building a Machine Learning Platform that automates the collection, processing, and evaluation of data, reducing manual overhead and accelerating the entire ML lifecycle. The systems you create will drive continuous data integration, automated evaluation, and rapid deployment—impacting how thousands of Humanoid Robots perceive and act in the real world every day. Responsibilities
Automate data, inference, and auto-labeling pipelines Build the tooling and infrastructure for reporting and visualizing model metrics and performance Manage, analyze, and validate training and test datasets Coordinate with the team managing the hardware cluster to maintain high availability and jobs throughput for Machine Learning Drive implementation of best practices and monitoring systems to proactively detect and address issues in production Build and improve Python training infrastructure for stable and faster training and validate PyTorch models Qualifications
Strong programming experience in Python and vectorization APIs such as NumPy Experience with distributed compute systems (Kubernetes, Slurm, LSF, etc.) or experience with large datasets / data workflows Experience working in a team environment Experience with training deep learning models and designing and deploying automation systems for ML workflows is a plus Benefits & Compensation
Expected Compensation: $140,000 - $420,000 annual salary + cash and stock awards + benefits. Pay offered may vary based on location, knowledge, skills, and experience. Details of participation in benefit plans provided with offer. Aetna medical plans and HSA options Dental and vision plans with low or zero payroll deductions 401(k) with employer match and Employee Stock Purchase Plan Life, AD&D, disability insurance; Employee Assistance Program Sick and vacation time, holidays; flexible scheduling for salaried roles Dependent care FSA; commuter benefits Voluntary benefits (critical illness, hospital indemnity, accident, legal services, pet insurance) Tesla Babies program and other family support resources
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Join to apply for the Machine Learning Systems Engineer, Tooling & Infrastructure, Optimus role at Tesla. Get AI-powered advice on this job and more exclusive features. What To Expect
As a Software Engineer for the Optimus team, you will build the tools and infrastructure to make and measure improvements to neural network architecture by building and automating scalable data and inference pipelines, ensuring data quality by building visualizing tools. We are building a Machine Learning Platform that automates the collection, processing, and evaluation of data, reducing manual overhead and accelerating the entire ML lifecycle. The systems you create will drive continuous data integration, automated evaluation, and rapid deployment—impacting how thousands of Humanoid Robots perceive and act in the real world every day. Responsibilities
Automate data, inference, and auto-labeling pipelines Build the tooling and infrastructure for reporting and visualizing model metrics and performance Manage, analyze, and validate training and test datasets Coordinate with the team managing the hardware cluster to maintain high availability and jobs throughput for Machine Learning Drive implementation of best practices and monitoring systems to proactively detect and address issues in production Build and improve Python training infrastructure for stable and faster training and validate PyTorch models Qualifications
Strong programming experience in Python and vectorization APIs such as NumPy Experience with distributed compute systems (Kubernetes, Slurm, LSF, etc.) or experience with large datasets / data workflows Experience working in a team environment Experience with training deep learning models and designing and deploying automation systems for ML workflows is a plus Benefits & Compensation
Expected Compensation: $140,000 - $420,000 annual salary + cash and stock awards + benefits. Pay offered may vary based on location, knowledge, skills, and experience. Details of participation in benefit plans provided with offer. Aetna medical plans and HSA options Dental and vision plans with low or zero payroll deductions 401(k) with employer match and Employee Stock Purchase Plan Life, AD&D, disability insurance; Employee Assistance Program Sick and vacation time, holidays; flexible scheduling for salaried roles Dependent care FSA; commuter benefits Voluntary benefits (critical illness, hospital indemnity, accident, legal services, pet insurance) Tesla Babies program and other family support resources
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