Software Engineer, On-Device Machine Learning

Google Inc.; Sunnyvale (CA); On-site; USD 147,000 - 210,000; Full time

Job summary

Google Inc. in Sunnyvale, CA, is seeking a Software Engineer focused on On-Device Machine Learning to advance LiteRT and edge AI across Google products.

The role emphasizes implementing and optimizing ML models for mobile and embedded platforms, with opportunities to collaborate across teams and mentor junior engineers. The candidate will deploy and optimize models on-device, work with accelerators like GPU/TPU/NPUs, and contribute to infrastructure supporting on-device AI at scale.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
• 2 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
• Experience with runtimes and performance tuning.

Responsibilities

• Collaborate with peers through design and code reviews to ensure best practices.
• Implement solutions in ML areas, utilize ML infrastructure, and contribute to model optimization and data processing.
• Develop LiteRT, Google’s on-device AI framework for first- and third-party use cases.
• Enable on-device deployment of models across accelerators (GPU/Pixel TPU/NPUs/CPU).
• Improve performance of on-device model inference via runtime and kernel optimizations.

Skills

Problem solving

Mentoring

Software development

Education

Bachelor’s degree

Master’s degree preferred

Tools

PyTorch

TensorFlow

JAX

Core ML

Job description

Software Engineer, On-Device Machine Learning

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Google Sunnyvale, CA, USA

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

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X In most instances, this position requires in-person interviews as part of the hiring process.

• Bachelor’s degree or equivalent practical experience.
• 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
• 2 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
• Experience with runtimes and performance tuning.

Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical fields.
• Experience in ML frameworks (e.g., PyTorch, JAX, TensorFlow).
• Experience with on-device ML SDKs/tooling (e.g., TensorFlow Lite, ExecuTorch, Core ML, SNPE/QNN).
• Strong understanding of Generative AI model architectures and their optimization for on-device execution.
• Passion for innovation and a strong desire to push the boundaries of what's possible with on-device ML.

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.

LiteRT is Google’s on-device AI framework, succeeding TensorFlow Lite (TFLite). It improves the performance, efficiency, and portability of ML models across edge devices from mobile phones to embedded systems. LiteRT significantly upgrades GPU acceleration and introduces native NPU acceleration, while maintaining and enhancing the robust CPU performance inherited from TFLite.

LiteRT enables developers and Google products to deploy AI across mobile, web, desktop, and embedded. Our team focuses on building cross-platform infrastructure aligned with Google's business needs, serving Google products (Android, Chrome, Photos, Meet, YouTube, etc.), third-party developers, and specialized Pixel solutions. Our goal is to provide on-device AI infrastructure with exceptional performance, enabling framework and device flexibility at scale.

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. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

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.

LiteRT is Google’s on-device AI framework, succeeding TensorFlow Lite (TFLite). It improves the performance, efficiency, and portability of ML models across edge devices from mobile phones to embedded systems. LiteRT significantly upgrades GPU acceleration and introduces native NPU acceleration, while maintaining and enhancing the robust CPU performance inherited from TFLite.

LiteRT enables developers and Google products to deploy AI across mobile, web, desktop, and embedded. Our team focuses on building cross-platform infrastructure aligned with Google's business needs, serving Google products (Android, Chrome, Photos, Meet, YouTube, etc.), third-party developers, and specialized Pixel solutions. Our goal is to provide on-device AI infrastructure with exceptional performance, enabling framework and device flexibility at scale.

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. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google .

• Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
• Implement solutions in one or more specialized ML areas, utilize ML infrastructure, and contribute to model optimization and data processing.
• DevelopLiteRT, Google's on-device AI framework for first- and third-party, enabling SOTA hardware acceleration and use cases on edge platforms.
• Enable on-device deployment of key models, such asGemini NanoandGemma, across various accelerators (GPU/Pixel TPU/NPUs/CPU) on Android, Chrome, iOS, desktop, and more.
• Improve performance of on-device model inference via optimizations in on-device runtime and kernel implementation.

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 or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire .

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

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