AI Compute Architect, AI Hardware

Overview

The Tesla AI Hardware team is at the forefront of revolutionizing artificial intelligence through cutting-edge hardware innovation. The team designs and develops advanced AI chips to accelerate Tesla's machine learning capabilities, powering the neural networks behind Full Self-Driving (FSD) and Optimus. By creating custom silicon and optimized architectures, the team aims to keep Tesla a leader in AI-driven automotive and energy solutions.

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 AI and ML applications. This role involves hardware-software co-design, accelerator development, and distributed systems engineering to create efficient, scalable solutions that power cutting-edge AI workloads. The ideal candidate balances performance, power, and scalability, delivering simple yet high-impact implementations that accelerate Tesla's AI initiatives.

• Design and architect comprehensive end-to-end compute infrastructure for AI/ML pipelines, encompassing hardware specifications, system topologies, and custom accelerators
• Collaborate with system architects, micro-architects, IP vendors, and program management to guide SoC (System-on-Chip) development from concept 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

• 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

Along with competitive pay, as a full-time Tesla employee, you are eligible for the following benefits at day 1 of hire:

• Medical plans with multiple options and zero payroll deduction
• Family-building, fertility, adoption and surrogacy benefits
• Dental (including orthodontic coverage) and vision plans, both with zero paycheck contribution
• Company Paid HSA contribution when enrolled in the High-Deductible medical plan with HSA
• Healthcare and Dependent Care Flexible Spending…