Tesla

Makes electric cars, robotaxis and grid batteries

SI Infrastructure Engineer - Distributed Training, Optimus

Applied Machine LearningConfirmed live in the last 24 hours

Full-timePalo Alto, CA, USANo salary listedIn-person

About the Job

Requirements

Practical experience programming in Python and/or C++.
Proficiency in system-level software, particularly hardware-software interactions and resource utilization.
Understanding of modern machine learning concepts and state-of-the-art deep learning.
Experience working with training frameworks, ideally PyTorch.
Demonstrated experience scaling neural network training jobs across clusters of GPUs.

Responsibilities

Build and improve Python training infrastructure for stable and faster training.
Build tooling and infrastructure for reporting and visualizing model metrics and performance.
Build pipelines to run and validate PyTorch models.
Manage, analyze, and visualize training and test datasets.
Coordinate with the team managing the hardware cluster to maintain high availability and job throughput for machine learning.
Build and improve tooling to deploy trained neural networks to Tesla hardware.

Desired Qualifications

Previous experience in deep learning deployment.
Experience profiling and optimizing CPU-GPU interactions, including pipelining compute and transfers.

Category	Tesla AI
Location	Palo Alto, California
Requisition ID	231772
Type	Full-time

Job Description

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 the bot, and evaluate experimental results. You will help us automate the entire workflows of training, validation, and production of the Optimus. Most importantly, you will see your work repeatedly shipped to and utilized by thousands of Humanoid Robots in real world applications.

Job Responsibilities

Build and improve our Python training infrastructure for stable and faster training

Build the tooling and infrastructure for reporting and visualizing model metrics and performance

Build the pipelines to run and validate our PyTorch models

Manage, analyze, and visualize our training and test datasets

Coordinate with the team managing the hardware cluster to maintain high availability / jobs throughput for Machine Learning

Build and improve tooling to deploy trained neural nets to Tesla hardware

Job Requirements

Practical experience programming in Python and/or C++

Proficient in system-level software, particularly hardware-software interactions and resource utilization

Understanding of modern machine learning concepts and state of the art deep learning

Experience working with training frameworks, ideally PyTorch

Demonstrated experience scaling neural network training jobs across clusters of GPU’s

Optional: Previous experience in deep learning deployment

Optional: Profiling and optimizing CPU-GPU interactions (pipelining compute/transfers, etc)

About the Company

Tesla

Makes electric cars, robotaxis and grid batteries

Tesla makes electric cars and batteries that store power for homes and utilities, and it develops self-driving software and humanoid robots. In 2023, its Model Y became the first electric vehicle to rank as the world's best-selling car. Buyers order the Model 3 sedan, Model Y SUV, or Cybertruck pickup directly from Tesla instead of through dealers, and they charge on its Supercharger fast-charging network. It also sells Megapack and Powerwall batteries, runs a robotaxi service, and charges drivers a monthly fee for self-driving software that still needs their supervision. Tesla was founded in 2003, with Elon Musk as its lead early investor and a recognized co-founder, and it is based in Austin, Texas.

Company size: 10,001+
Company stage: IPO
Headquarters: Austin, TX
Founded: 2003

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