Software Engineer, GDC LLM Serving and GPU Performance
Indexed description
- Health, dental, vision, life, disability insurance
- Retirement Benefits: 401(k) with company match
- Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
- Sick Time: 40 hours/year (statutory, where applicable); 5 days/event (discretionary)
- Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
- Baby Bonding Leave: 18 weeks
- Holidays: 13 paid days per year.
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
- 5 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
- 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 8 years of experience with data structures and algorithms.
- 3 years of experience in a technical leadership role leading project teams and setting technical direction.
- 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
Want to shape the future of how Google serves its most advanced Large Language Models? Join the GDC AI Models and Performance team and work on AI infrastructure.
Imagine re-inventing LLM serving by contributing to our disaggregated serving initiatives – separating compute and memory to unlock new levels of performance and flexibility. You could be optimizing Key-Value (KV) cache transfer mechanisms, designing dynamic resource allocation strategies, or building the next generation of performance analysis tools to dissect and enhance GPU utilization. This is a unique opportunity to go deep, from system-level design down to performance profiling, ensuring Google's LLMs run faster and more cost-effectively than ever before.
The US base salary range for this full-time position is $207,000-$300,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. 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 benefits at Google .
Responsibilities
- Design, develop, and implement enhancements to the LLM serving stack, focusing on performance, scalability, and resource efficiency (e.g., on systems like Wiz, Servomatic).
- Contribute to the design and implementation of advanced serving architectures, including disaggregated serving.
- Build and maintain infrastructure and tooling for in-depth performance analysis, profiling, and benchmarking of LLM models on GPU accelerators.
- Identify and address performance bottlenecks across the stack, working closely with teams providing core GPU libraries and kernels.
- Collaborate with research, engineering, and SRE teams to optimize and deploy LLMs in production.
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