Job Description

Locations

• Palo Alto, California, United States

Salary

Skills Required

• performance modelingintermediate
• hardware architectureintermediate
• ML accelerationintermediate
• AI acceleratorsintermediate
• GPU/CPU architecturesintermediate
• memory hierarchiesintermediate
• parallel computingintermediate
• Python/C++ for modeling, analysis, and automationintermediate
• ML frameworksintermediate
• neural network architecturesintermediate
• compiler optimizationsintermediate
• ML graph loweringintermediate

Required Qualifications

• Degree in Engineering, Computer Science, or equivalent in experience and evidence of exceptional ability (experience)
• Previous industry/research experience in performance modeling, hardware architecture, or ML acceleration (experience)
• Strong understanding of AI accelerators, GPU/CPU architectures, memory hierarchies, and parallel computing (experience)
• Proficiency in Python/C++ for modeling, analysis, and automation; familiarity with ML frameworks (experience)
• Knowledge of neural network architectures and their computational demands (experience)
• Proven ability to work with hardware/software teams to translate algorithmic needs into hardware features (experience)
• Clear documentation and presentation skills for technical and non-technical stakeholders (experience)

Preferred Qualifications

• Knowledge of compiler optimizations or ML graph lowering is a plus (experience)

Responsibilities

• Develop performance models and simulation tools to evaluate hardware architectures for machine learning workloads
• Analyze and optimize neural network performance on current and next-gen AI accelerators
• Collaborate with hardware architects and software teams to identify bottlenecks, propose architectural improvements, and validate design trade-offs
• Create benchmarking frameworks to assess performance, power, and latency of ML workloads
• Conduct pre- and post-silicon performance analysis to correlate models with real-world hardware behavior
• Drive hardware-software co-optimization by translating neural network trends into architectural requirements
• Document and communicate findings to cross-functional teams to guide future hardware roadmaps

Benefits

• general: Aetna PPO and HSA plans > 2 medical plan options with $0 payroll deduction
• general: Family-building, fertility, adoption and surrogacy benefits
• general: Dental (including orthodontic coverage) and vision plans, both have options with a $0 paycheck contribution
• general: Company Paid (Health Savings Account) HSA Contribution when enrolled in the High Deductible Aetna medical plan with HSA
• general: Healthcare and Dependent Care Flexible Spending Accounts (FSA)
• general: 401(k) with employer match, Employee Stock Purchase Plans, and other financial benefits
• general: Company paid Basic Life, AD&D, short-term and long-term disability insurance
• general: Employee Assistance Program
• general: Sick and Vacation time (Flex time for salary positions), and Paid Holidays
• general: Back-up childcare and parenting support resources
• general: Voluntary benefits to include: critical illness, hospital indemnity, accident insurance, theft & legal services, and pet insurance
• general: Weight Loss and Tobacco Cessation Programs
• general: Tesla Babies program
• general: Commuter benefits
• general: Employee discounts and perks program

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