Senior Machine Learning Engineer, Performance

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages.
• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
• 3 years of experience with performance, large-scale systems data analysis, visualization tools, or debugging.

Preferred qualifications:

• Master's degree or PhD in Computer Science or a related technical field.
• 5 years of experience with data structures and algorithms.
• 1 year of experience in a technical leadership role.
• Experience developing accessible technologies.

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.

We are part of ML Performance and deliver AI performance solutions at Google's unparalleled scale. We achieve this through deep fleet-wide analysis, building scaling automation, and providing last-mile optimization where customization is needed. Our work directly impacts critical models, like DeepSeek, Qwen, Gemini, Gemma, improving their performance on TPUs, bridging research with real-world, high-demand applications.

Our focus point is model's performance - we use various techniques that change AI models in order to improve their performance, while keeping quality high. It involves a combination of model design, performance analysis high- and low-level coding, compilers, and hardware design.

The Core team builds the technical foundation behind Google’s flagship products. We are owners and advocates for the underlying design elements, developer platforms, product components, and infrastructure at Google. These are the essential building blocks for excellent, safe, and coherent experiences for our users and drive the pace of innovation for every developer. We look across Google’s products to build central solutions, break down technical barriers and strengthen existing systems. As the Core team, we have a mandate and a unique opportunity to impact important technical decisions across the company.

The US base salary range for this full-time position is $174,000-$252,000 + 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.The US base salary range for this full-time position is $174,000-$252,000 + 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

• Analyze performance and efficiency metrics to identify bottlenecks.
• Engage with Google product teams, Cloud, researchers to solve their performance problems.
• Apply parallelization and optimization techniques, such as sharding, quantization, and sparsity, to improve model performance while meeting pre-defined quality characteristics.
• Analyze and debug performance.