Machine Learning Kernel Performance Engineer, Dojo

28 Days Old

Machine Learning Kernel Performance Engineer, Dojo Join to apply for the Machine Learning Kernel Performance Engineer, Dojo role at Tesla Machine Learning Kernel Performance Engineer, Dojo Join to apply for the Machine Learning Kernel Performance Engineer, Dojo role at Tesla Get AI-powered advice on this job and more exclusive features. What To Expect As a member of the Dojo Machine Learning software team, you will be responsible for developing and optimizing machine learning kernels to run on a massively parallel machine. The ideal candidate will have a strong background in kernel development and performance optimization for AI workloads, with a passion for delivering high-performance implementations, which are simple to use.
What You'll Do
Develop and validate datapath kernels on a massively parallel machine Design and deliver implementations of known neural network algorithms on Dojo Hardware, for both training and inference workloads Collaborate with architects and compiler engineers to transfer kernel designs to the Dojo compiler and production environment Work closely with the team to drive improvements to the kernel development framework, supporting environments, and other components of the system Work with hardware and simulations teams to ensure future hardware generations optimally satisfy algorithmic requirements Participate in code reviews, testing, and debugging to ensure high-quality software Stay up to date with the latest developments in AI workloads, domain-specific languages, computer architecture, and simulation techniques
What You'll Bring
Degree in Engineering, Computer Science, or equivalent in experience and evidence of exceptional ability 3+ years of experience in kernel development In depth understanding of Large Language Models (LLMs), transformer architectures, their training, inference, and optimization Strong programming skills in languages such as C/C++ and/or Python Experience with deep learning frameworks such as PyTorch, JAX, Pallas etc. Strong understanding of CPU and/or GPU microarchitecture, including pipelining, caching, and memory hierarchy Excellent problem-solving skills, with the ability to analyze complex problems and develop creative solutions Strong communication and collaboration skills, with the ability to work effectively with architects, engineers, and researchers Able to work from Tesla’s Palo Alto office
Benefits Compensation and Benefits Along 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 deduction Family-building, fertility, adoption and surrogacy benefits Dental (including orthodontic coverage) and vision plans, both have options with a $0 paycheck contribution Company Paid (Health Savings Account) HSA Contribution when enrolled in the High Deductible Aetna medical plan with HSA Healthcare and Dependent Care Flexible Spending Accounts (FSA) 401(k) with employer match, Employee Stock Purchase Plans, and other financial benefits Company paid Basic Life, AD&D, short-term and long-term disability insurance Employee Assistance Program Sick and Vacation time (Flex time for salary positions), and Paid Holidays Back-up childcare and parenting support resources Voluntary benefits to include: critical illness, hospital indemnity, accident insurance, theft & legal services, and pet insurance Weight Loss and Tobacco Cessation Programs Tesla Babies program Commuter benefits Employee discounts and perks program
Expected Compensation
$132,000 - $390,000/annual salary + cash and stock awards + benefits
Pay 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.
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Location:
Palo Alto, CA, United States
Job Type:
FullTime
Category:
Computer And Mathematical Occupations

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