Tesla

Makes electric cars, robotaxis and grid batteries

Kernel Optimization Software Engineer - SI Hardware

Applied Machine LearningConfirmed live in the last 24 hours

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

About the Job

Requirements

Hands-on experience with kernel optimization, distributed systems, inference runtimes, or serving frameworks.
Experience with large language models, transformers, state space models, diffusion models, and convolutional neural networks, including their performance characteristics.
Familiarity with performance modeling and roofline analysis.
Understanding of computer and graphics processing unit architecture, single instruction multiple data, multithreading, and/or other accelerators with vectorized instructions.
A degree in Engineering or Computer Science, or equivalent experience and evidence of exceptional ability.
Strong analytical and debugging skills.
Ability to work across team boundaries with compiler, hardware, and machine learning teams.

Responsibilities

Implement, optimize, and profile high-performance kernels for inference and training on Tesla's SI and Dojo application-specific integrated circuits.
Optimize bottlenecks in the inference flow, make precision/performance tradeoff decisions, and develop novel techniques to improve hardware utilization and throughput.
Work on edge and datacenter workloads, from small encoders and decoders to distributed large language model inference.
Work with hardware teams to shape next-generation Tesla hardware by evaluating architectural tradeoffs and balancing performance with versatility.
Research and implement state-of-the-art machine learning techniques to achieve high performance on Tesla hardware.
Experiment with numerical methods and alternative architectures.
Collaborate with the compiler team on programmability and performance.

Desired Qualifications

Contributions to machine learning serving frameworks, compilers, and frameworks, such as SGLang, LLVM, PyTorch, or MLIR.

Category	Tesla SI
Location	Palo Alto, California
Requisition ID	270313
Type	Full-time

Job Description

<div class="MSWordContent"><p>The Performance Optimization team takes research models and makes them run efficiently on Tesla's SI-ASICs, powering Autopilot and Optimus. This role sits at the intersection of SI research, compiler development, kernel optimization, and hardware design. You'll collaborate with SI researchers on novel quantization techniques, precision improvements, and non-standard architectures. You'll develop optimized kernels using our MLIR-based compiler stack to achieve real-time latency for self-driving and humanoid robots. You'll work directly with hardware teams to shape our next-generation SI5, SI6, and Dojo3 chips.</div>

Job Responsibilities

Implement, optimize, and profile highly performant kernels for inference and training on Tesla's SI and Dojo ASICs
Optimize bottlenecks in the inference flow, make precision/performance tradeoff decisions, and develop novel techniques to improve hardware utilization and throughput
Work on a variety of edge and datacenter workloads, from small encoders/decoders to distributed LLM inference
Work with hardware teams to shape the next generation of Tesla hardware, evaluating architectural tradeoffs and balancing performance with versatility
Research and implement state-of-the-art machine learning techniques to achieve high performance on our hardware
Experiment with numerical methods and alternative architectures
Collaborate with the compiler team on programmability and performance

Job Requirements

Hands-on experience with kernel optimization, distributed systems, inference runtimes, or serving frameworks
Experience with LLMs, transformers, state space models, diffusion models, CNNs, and their performance characteristics
Familiarity with performance modeling and roofline analysis
Understanding of computer and GPU architecture, SIMD, multithreading, and/or other accelerators with vectorized instructions
Strong analytical and debugging skills
Ability to work across team boundaries with compiler, hardware, and ML teams
Degree in Engineering, Computer Science, or equivalent in experience and evidence of exceptional ability
Contributions to ML serving frameworks, compilers, and frameworks is a bonus (e.g. SGLang, LLVM, PyTorch, MLIR)

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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