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Staff Software Engineer, ML Performance, GPUs

California, United States (On-site)

Staff Software Engineer, ML Performance, GPUs

3 Weeks ago • 8-13 Years • Artificial Intelligence • $189,000 PA - $284,000 PA

About the job

6 skills required for this role

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tensorflow

algorithms

data-structures

model-deployment

networking

talent-acquisition

Job Description

This Staff Software Engineer role focuses on optimizing the performance of Large Language Models (LLMs) on Google's GPU infrastructure. Responsibilities include analyzing LLM performance, identifying bottlenecks, and implementing solutions to improve training and serving efficiency. The role requires extensive experience in software development, ML infrastructure optimization, GPU programming, and performance analysis. The engineer will collaborate with various Google product teams (Gemini, Search, Cloud LLM, APIs) to onboard new LLMs and enable large-scale training. They will also conduct architecture-level simulations and roofline analysis to guide optimization efforts. The ideal candidate will possess strong problem-solving skills and a deep understanding of ML systems and GPU architectures.

Must have:

8+ years software development experience
5+ years ML design & infrastructure optimization
Experience with performance analysis and GPU programming
Experience testing and launching software products
Software design and architecture experience

Good to have:

Master's or PhD in related field
Experience with TensorFlow or other ML tools
Compiler optimization experience
Experience in complex organizations
Architecture analysis and optimization

Minimum qualifications:

Bachelor’s degree or equivalent practical experience.
8 years of experience in software development, and with data structures/algorithms.
5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
Experience with performance analysis and GPU programming.

Preferred qualifications:

Master’s degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience.
5 years of experience working in a complex, matrixed organization.
Experience with machine learning systems (e.g., background theory, TensorFlow, or other ML tools).
Experience working on compiler optimizations or related fields.
Experience with architecture analysis and optimization.

About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

The US base salary range for this full-time position is $189,000-$284,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about .

Responsibilities

Analyse Large Language Model (LLM) performance and optimizations for partner teams including Google Gemini, Search, Cloud LLM and Application programming interfaces (APIs).
Identify and maintain LLM training and serving benchmarks, and use them to identify performance opportunities and drive XLA:GPU/Triton performance and to guide future XLA releases.
Engage with Google product teams, to solve their ML model performance challenges, including onboarding new LLM models and products onto Google’s GPU hardware and enabling LLMs to train efficiently on a very large scale (i.e., thousands of GPUs).
Run architecture-level simulations on GPU designs and perform roofline analysis to guide partner teams.
Analyze performance and efficiency metrics to identify bottlenecks, design, and implement solutions.

View Full Job Description

$189.0K - $284.0K/yr (Outscal est.)

$236.5K/yr avg.

Mountain View, California, United States

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About The Company

Google

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A problem isn't truly solved until it's solved for all. Googlers build products that help create opportunities for everyone, whether down the street or across the globe. Bring your insight, imagination and a healthy disregard for the impossible. Bring everything that makes you unique. Together, we can build for everyone.