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# Software Engineer, Performance Modeling, SI Hardware

- **Company:** Tesla Motors
- **Location:** Palo Alto, CA, United States
- **Salary:** $140,000.0
- **Contract:** Permanent contract
- **Skills:** C++ (Programming Language), Software Quality, Code Review, Computer Programming, Software Debugging, Hardware Design, Python (Programming Language), Machine Learning, Pytorch, Large Language Models, Deep Learning, Information Technology, Optimization Algorithms, Transformer Architectures, Hardware Acceleration, Physical Design
- **Published:** October 15, 2026
- **Apply:** https://jobs.localjobnetwork.com/apply/add/87434500/1

## About the Role

* Degree in Engineering, Computer Science, or a related field, or equivalent practical experience demonstrating exceptional ability
 * In-depth knowledge of Large Language Models (LLMs), transformer architectures, including their training, inference processes, and optimization techniques
 * Strong expertise in CPU, GPU, and/or ML accelerator microarchitectures, with hands-on experience in performance characterization
 * Proficiency with deep learning frameworks such as PyTorch, JAX, Pallas, or similar tools
 * Robust programming skills in C/C++, Python, or other relevant languages
 * Solid understanding of physical design constraints, including power, performance, and area (PPA) tradeoffs in hardware development
 * Exceptional problem-solving abilities, capable of dissecting complex issues and devising innovative, practical solutions
 * Excellent communication and interpersonal skills, fostering effective collaboration across teams, including leadership and engineering stakeholders
 * Demonstrated experience in performance analysis, including the use of simulation frameworks and profiling tools

## Description

As a key member of the Tesla SI hardware team, the SI/ML Modeling Engineer will drive the modeling, and optimization of next-generation tensor compute hardware. This role requires a deep expertise in computer architecture, and proven proficiency in performance modeling and optimization. The ideal candidate has a thorough understanding of SI workloads, and thrives in fast-paced environments, delivering elegant, high-performance solutions that push the boundaries of AI hardware efficiency.
What You'll Do

 * Collaborate closely with system architects, micro architects, ML model designers, and compiler engineers to create highly efficient hardware designs on accelerated timelines
 * Develop and validate sophisticated performance models to evaluate architecture and microarchitecture tradeoffs, guiding informed decision-making
 * Define comprehensive workload suites and key performance metrics to benchmark and evaluate hardware capabilities
 * Analyze and assess implementations of machine learning algorithms on Tesla SI hardware, identifying bottlenecks and opportunities for improvement
 * Participate in hardware/software co-design efforts to align future hardware capabilities with evolving algorithmic demands
 * Contribute to code reviews, testing, and debugging processes to maintain exceptional code quality and reliability
 * Stay abreast of cutting-edge advancements in SI workloads, domain-specific languages, computer architecture, and simulation methodologies to inform strategic directions