T
AI Compute Architect, AI Hardware
Accepting applicationsTesla · Palo Alto, CA
Full-Time Mid_senior AIC++PythonSicSoC
Posted
28 May
Category
Test
Experience
Mid_senior
Country
United States
What To Expect
The Tesla AI Hardware team is at the forefront of revolutionizing artificial intelligence through cutting-edge hardware innovation. Comprising brilliant engineers and visionaries, the team designs and develops advanced AI inference chips tailored to accelerate Tesla’s machine learning capabilities. A key part of this effort is Dojo, Tesla's custom supercomputer system built to efficiently train massive neural networks on vast video data from the fleet. The work of Tesla's AI Hardware team powers the neural networks behind Full Self-Driving (FSD), and Tesla humanoid robot, Optimus, pushing the boundaries of computational efficiency and performance. By creating custom silicon and optimized architectures, the team ensures Tesla remains a leader in AI-driven automotive and energy solutions, shaping a future where intelligent machines enhance human life.
As a key member of the Tesla AI hardware team, the AI/ML Compute Architect will drive the innovation and optimization of computing architectures tailored for artificial intelligence and machine learning applications. This role involves visionary hardware-software co-design, accelerator development, and distributed systems engineering to create efficient, scalable solutions that power cutting-edge AI workloads. The ideal candidate is a strategic thinker with proven expertise in balancing performance, power, and scalability, delivering simple yet high-impact implementations that accelerate Tesla's AI initiatives.
What You'll Do
Design and architect comprehensive end-to-end compute infrastructure for AI/ML pipelines, encompassing hardware specifications, system topologies, and custom accelerators
Collaborate closely with system architects, micro architects, IP vendors, and program management to guide SoC (System-on-Chip) development from initial concept through to production-ready implementation
Optimize the interplay between compute, storage, and interconnect to maximize throughput, minimize latency, and reduce energy consumption across training and inference scenarios
Partner with ML model designers, compiler engineers, and software developers to build intuitive tools, frameworks, and abstractions that streamline the deployment and scaling of AI/ML workloads
Lead performance modeling initiatives, simulating architecture and microarchitecture tradeoffs to inform design decisions and predict system behavior under real-world conditions
Evaluate emerging technologies, such as novel accelerators or interconnect fabrics, and prototype innovative architectures to anticipate and address evolving AI compute demands
Maintain expertise in the latest advancements in AI workloads, domain-specific languages (e.g., for ML optimization), computer architecture principles, and advanced simulation methodologies
What You'll Bring
Degree in Electrical Engineering, Computer Science, Computer Engineering, or a related field; or equivalent practical experience demonstrating exceptional ability
Deep knowledge of CPU, GPU, and ML accelerator microarchitectures, including their design principles and performance characteristics
Strong understanding of Large Language Models (LLMs), transformer-based architectures, and techniques for their training, inference, quantization, and optimization
Proficiency in analyzing physical design constraints, including power, performance, and area (PPA) tradeoffs in hardware systems
Exceptional problem-solving abilities, with a track record of dissecting complex technical challenges and devising innovative, practical solutions
Hands-on experience with deep learning frameworks like PyTorch, JAX, Pallas, or similar tools for model development and optimization
Excellent interpersonal and communication skills, enabling effective collaboration across diverse teams, from leadership to individual contributors
Prior experience in performance analysis, including the use of simulation frameworks (e.g., gem5, SST) to model and benchmark systems
Ability to work on-site at Tesla’s Palo Alto office, contributing to a fast-paced, collaborative environment
Proficiency in programming languages such as C/C++ and Python, with applications in hardware simulation, modeling, or system-level software
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:
Medical plans > 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 Accounts) HSA Contribution when enrolled in the High-Deductible 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 (90 day waiting period)
Employee Assistance Program
Sick and Vacation time (Flex time for salary positions, Accrued hours for Hourly 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
$128,000 - $312,000/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.
, Tesla
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The Tesla AI Hardware team is at the forefront of revolutionizing artificial intelligence through cutting-edge hardware innovation. Comprising brilliant engineers and visionaries, the team designs and develops advanced AI inference chips tailored to accelerate Tesla’s machine learning capabilities. A key part of this effort is Dojo, Tesla's custom supercomputer system built to efficiently train massive neural networks on vast video data from the fleet. The work of Tesla's AI Hardware team powers the neural networks behind Full Self-Driving (FSD), and Tesla humanoid robot, Optimus, pushing the boundaries of computational efficiency and performance. By creating custom silicon and optimized architectures, the team ensures Tesla remains a leader in AI-driven automotive and energy solutions, shaping a future where intelligent machines enhance human life.
As a key member of the Tesla AI hardware team, the AI/ML Compute Architect will drive the innovation and optimization of computing architectures tailored for artificial intelligence and machine learning applications. This role involves visionary hardware-software co-design, accelerator development, and distributed systems engineering to create efficient, scalable solutions that power cutting-edge AI workloads. The ideal candidate is a strategic thinker with proven expertise in balancing performance, power, and scalability, delivering simple yet high-impact implementations that accelerate Tesla's AI initiatives.
What You'll Do
Design and architect comprehensive end-to-end compute infrastructure for AI/ML pipelines, encompassing hardware specifications, system topologies, and custom accelerators
Collaborate closely with system architects, micro architects, IP vendors, and program management to guide SoC (System-on-Chip) development from initial concept through to production-ready implementation
Optimize the interplay between compute, storage, and interconnect to maximize throughput, minimize latency, and reduce energy consumption across training and inference scenarios
Partner with ML model designers, compiler engineers, and software developers to build intuitive tools, frameworks, and abstractions that streamline the deployment and scaling of AI/ML workloads
Lead performance modeling initiatives, simulating architecture and microarchitecture tradeoffs to inform design decisions and predict system behavior under real-world conditions
Evaluate emerging technologies, such as novel accelerators or interconnect fabrics, and prototype innovative architectures to anticipate and address evolving AI compute demands
Maintain expertise in the latest advancements in AI workloads, domain-specific languages (e.g., for ML optimization), computer architecture principles, and advanced simulation methodologies
What You'll Bring
Degree in Electrical Engineering, Computer Science, Computer Engineering, or a related field; or equivalent practical experience demonstrating exceptional ability
Deep knowledge of CPU, GPU, and ML accelerator microarchitectures, including their design principles and performance characteristics
Strong understanding of Large Language Models (LLMs), transformer-based architectures, and techniques for their training, inference, quantization, and optimization
Proficiency in analyzing physical design constraints, including power, performance, and area (PPA) tradeoffs in hardware systems
Exceptional problem-solving abilities, with a track record of dissecting complex technical challenges and devising innovative, practical solutions
Hands-on experience with deep learning frameworks like PyTorch, JAX, Pallas, or similar tools for model development and optimization
Excellent interpersonal and communication skills, enabling effective collaboration across diverse teams, from leadership to individual contributors
Prior experience in performance analysis, including the use of simulation frameworks (e.g., gem5, SST) to model and benchmark systems
Ability to work on-site at Tesla’s Palo Alto office, contributing to a fast-paced, collaborative environment
Proficiency in programming languages such as C/C++ and Python, with applications in hardware simulation, modeling, or system-level software
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:
Medical plans > 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 Accounts) HSA Contribution when enrolled in the High-Deductible 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 (90 day waiting period)
Employee Assistance Program
Sick and Vacation time (Flex time for salary positions, Accrued hours for Hourly 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
$128,000 - $312,000/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.
, Tesla
Show more Show less