Software Engineering Manager, GPU Performance

Minimum qualifications:

1. Bachelor’s degree or equivalent practical experience.
2. 8 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
3. 5 years of experience leading in Machine Learning (ML) design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
4. 3 years of experience in a technical leadership role, overseeing projects, with 2 years of experience in a people management, supervision/team leadership role.
5. Experience with Performance Analysis, Graphics Processing Unit (GPU) Programming, Machine Learning algorithms and tools.

Preferred qualifications:

1. Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
2. 3 years of experience working in an organization involving cross-functional, or cross-business projects.
3. Experience with Compute Unified Device Architecture (CUDA), Performance Optimization and GPU Hardware Architecture.

As a Software Engineering Manager, you will not only have the technical expertise to provide leadership to major projects but also manage a team of Engineers. You will optimize your own code and ensure that Engineers are able to optimize theirs. You will manage project goals, contribute to product strategy, and help develop your team.

In this role, you will optimize, model, and evaluate Graphics Processing Unit (GPU) systems for comparative analysis for Google’s internal Machine Learning (ML) workloads. You will extract efficiency in Google’s GPU fleet and focus on performance analysis and optimization to identify opportunities in Google production and research ML workloads. You will evaluate ML workloads and run performance/Technical Case Owner simulations to collect roofline estimates and guide decisions for the Cloud hardware teams. You will focus on Large Language Models (LLM) performance analysis and optimizations for GPU.

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.

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. 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 benefits at Google (https://careers.google.com/benefits/).

Responsibilities:

1. Set and communicate team priorities that support the broader organization's goals.
2. Set clear expectations with individuals based on their level and role.
3. Develop the technical goal and roadmap within the scope of your team(s).
4. Lead the design and implementation of solutions in specialized Machine Learning (ML) areas.
5. Maintain Large Language Models (LLM) training and serving benchmarks to identify performance opportunities.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. See also https://careers.google.com/eeo/.

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