Tesla

Makes electric cars, robotaxis and grid batteries

Software Engineer - Training Performance, SI Infrastructure

Applied Machine LearningConfirmed live in the last 24 hours

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

About the Job

Requirements

Members of the Autopilot AI Infrastructure team are expected to be adaptable to the dynamic requirements of AI research and capable of contributing across all parts of the AI training software stack.
Practical experience programming in Python and/or C/C++ is required.
Experience programming in CUDA, cuDNN, or Triton, particularly in the context of operations used in AI workloads, is required.
Experience profiling and optimizing CPU-GPU interactions, including pipelining computation with data transfers, is required.
Experience working with training frameworks, ideally PyTorch, is required.
Proficiency in system-level software, particularly hardware-software interactions and resource utilization, is required.
Experience with parallel programming concepts and primitives is required.
Understanding of modern machine learning concepts and state-of-the-art deep learning is required.
Experience scaling neural network training jobs across many GPUs is required.

Responsibilities

Reduce wall clock time to convergence of training jobs by identifying bottlenecks in the machine learning stack, from data loading up to the GPU.
Integrate efficient, low-level code with the overall high-level training framework.
Profile workloads and implement solutions to increase training efficiency.
Optimize workloads for efficient hardware utilization, including CPU and GPU compute, data throughput, and networking.

Category	Tesla SI
Location	Palo Alto, California
Requisition ID	285676
Type	Full-time

Job Description

<p>As a Software Engineer within the Autopilot SI Infrastructure team, you will work on reinforcing, optimizing, and scaling our infrastructure components supporting SI research activities for Autopilot and the Optimus. </p><p>At the core of our autonomy capabilities are neural networks that the research team is designing to train on very large amounts of data, across large-scale GPU clusters. Robustly training these models at scale and in the shortest amount of time is critical to our mission. </p>

Job Responsibilities

Reduce wall clock time to convergence of our training jobs by identifying bottlenecks in the ML stack, from data-loading up to the GPU
Integrate efficient, low-level code with the overall high-level training framework
Profile our workloads and implement solutions to increase training efficiency
Optimize workloads for efficient hardware utilization (e.g. CPU and GPU compute, data throughput, networking)

Job Requirements

Members of the Autopilot AI Infrastructure team are expected to be adaptable to the dynamic requirements of AI research and capable of contributing across all parts of the AI training software stack
Practical experience programming in Python and/or C/C++
Experience programming in CUDA, cuDNN or Triton, particularly in the context of operations used in AI workloads
Experience profiling and optimizing CPU-GPU interactions (pipelining computation with data transfers, etc.)
Experience working with training frameworks (ideally PyTorch)
Proficient in system-level software, in particular hardware-software interactions and resource utilization
Experience with parallel programming concepts and primitives
Understanding of modern machine learning concepts and state of the art deep learning
Experience scaling neural network training jobs across many GPUs

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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