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Senior Software Engineer, ML Compilers, Edge TPU

Google

Listing collected from Google's career site. NextChapter is independent of Google.

Mountain View, CA · $174k–$252k a year · Posted October 1, 2026

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Pay compared with the market

This listing pays about $213,000 a year. Across 1,464 open senior software engineer listings that state pay, the middle half runs $174,500 to $222,500 and the median is $202,500. That is inside the middle half of those listings, 5% above the median.

Listed pay is what employers advertise, not what people are paid.

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About the job

Senior Software Engineer, ML Compilers, Edge TPU Share Senior Software Engineer, ML Compilers, Edge TPU

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corporate_fare Google place Mountain View, CA, USA ; Kirkland, WA, USA

Mid Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area.

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info_outline X In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:

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 (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance

Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks

Baby Bonding Leave: 18 weeks

Holidays: 13 paid days per year

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; Kirkland, WA, USA .

Minimum qualifications:

Bachelor’s degree or equivalent practical experience.

5 years of experience with software development in one or more programming languages (e.g. C++).

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 compilers (optimization, parallelization, etc.).

Preferred qualifications:

Master's degree or PhD in Computer Science or a related technical field.

Compiler development experience in the context of accelerator-based architectures.

Experience working with low-level software or strong interest in developing low-level software.

Experience working with hardware such as CPU, GPU, or TPU.

Experience in optimizing ML model inference on device.

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.

As a Senior Software Engineer on the EdgeTPU Compiler team, you will play a key role in building next-generation compiler optimizations to power machine learning (ML) models on custom hardware. In this technical role, you will bridge the gap between ML models and hardware execution, translating framework-level code (JAX, PyTorch) into highly efficient instructions for the EdgeTPU.

You will own end-to-end features, from triaging complex performance and correctness issues to implementing robust, production-ready compiler optimizations. Additionally, you will collaborate cross-functionally with model owners to guide model design, work alongside stakeholders to shape the technical goal, and manage project deliverables to accelerate the deployment of ML experiences on edge devices.

Google's mission is to organize the world's information and make it universally accessible and useful. Our team combines the best of Google AI, Software, and Hardware to create radically helpful experiences. We research, design, and develop new technologies and hardware to make computing faster, seamless, and more powerful. We aim to make people's lives better through technology. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google .

Responsibilities

Design and build ML compiler optimizations for EdgeTPU hardware, and extend leading authoring frameworks (such as JAX and PyTorch) to enable seamless, high-performance compilation.

Triage, root-cause, and resolve complex correctness and performance issues encountered when deploying state-of-the-art ML models on EdgeTPU.

Propose, design, and implement robust compiler features and fixes to systematically address performance bottlenecks and hardware limitations.

Partner closely with ML model owners to influence model architectures, ensuring they are designed for optimal, efficient execution on EdgeTPU systems.

Own project execution from end to end, collaborating with cross-functional partners and stakeholders, and managing priorities/deadlines/deliverables for key compiler feature areas.

Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google's Applicant and Candidate Privacy Policy .

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy