Software Engineer, Performance, YouTube ML Efficiency

Google • San Bruno, CA

5h

About The Position

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.

At YouTube, we believe that everyone deserves to have a voice, and that the world is a better place when we listen, share, and build community through our stories. We work together to give everyone the power to share their story, explore what they love, and connect with one another in the process. Working at the intersection of cutting-edge technology and boundless creativity, we move at the speed of culture with a shared goal to show people the world. We explore new ideas, solve real problems, and have fun — and we do it all together.

The US base salary range for this full-time position is $141,000-$202,000 + 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 [https://careers.google.com/benefits/].

Requirements

• Bachelor’s degree or equivalent practical experience.
• 2 years of experience with software development in one or more programming languages.
• 2 years of experience with computer architecture, performance analysis, and performance modeling.
• 2 years of experience with performance, systems data analysis, visualization tools, or debugging.

Nice To Haves

• Master's degree or PhD in computer science or related technical fields.
• 2 years of experience with data structures and algorithms.
• Experience developing accessible technologies.
• Experience with GPU or TPU performance analysis.
• Experience with ML frameworks such as TensorFlow, JAX, and PyTorch, or ML compilers (e.g., accelerated linear algebra (XLA)).

Responsibilities

• Redesign components to improve efficiency, including implementing ragged tensors, scaling embedding tables, and developing new optimizers to change how models utilize resources.
• Partner with quality teams to enable foundational model changes. Identify and unblock performance detractors, allowing experimenters to scale model complexity and training procedures that were previously resource-prohibitive.
• Act as a local expert on TPU hardware. Push hardware limits by offloading logic to SparseCore, guiding model evaluation based on hardware constraints, and writing low-level Pallas kernels for maximum throughput.
• Address issues ranging from low-level infrastructure improvements and accelerated linear algebra (XLA) compiler tuning to leveraging application-level insights like traffic patterns and request deduping.
• Design self-tuning frameworks and analytics to automate performance tuning and resource attribution.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level