GPU Performance Modeling Engineer

Job Description

Google is seeking software engineers to work on next-generation technologies and large-scale infrastructure projects, with a focus on AI/ML, deep learning, and natural language processing.

Requirements

• Bachelor’s degree or equivalent practical experience
• 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree
• Master's degree or PhD in Computer Science or related technical fields
• 3 years of experience with LLMs/ML, algorithms and tools (e.g. TensorFlow/Jax), Artificial Intelligence, deep learning, or natural language processing
• 2 years of experience with data structures or algorithms in an academic or industry setting
• 2 years of experience building and developing large-scale infrastructure, distributed systems or networks, or with compute technologies, storage, or hardware architecture
• Experience in developing and deploying AI/ML models and algorithms with Python and other languages (e.g., C++, Kotlin, Java)
• Understanding of ML, data analysis, and developer tools

Responsibilities

• Identify and maintain Large Language Model (LLM) training and serving benchmarks
• Engage with Google product teams to solve ML model performance problems
• Run architecture level simulations on GPU designs and perform roofline analysis
• Analyze performance and efficiency metrics to identify bottlenecks and implement solutions

Benefits

• Employees at Google are often offered benefits like comprehensive health insurance, 401(k) matching, and flexible work arrangements, among other benefits.