Staff Software Engineer, Core ML Frameworks

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, and fine tuning).
• 5 years of experience testing and launching software products.
• 3 years of experience with software design and architecture.

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, a technical related field, or equivalent practical experience.
• 3 years of experience working in a complex, matrixed organization involving cross-functional or cross-business projects.
• 3 years of experience in a technical leadership role leading project teams and setting technical direction.
• Experience taking complex software projects from initial design and research through to production deployment and maintenance in a large-scale environment.
• Experience building foundational platforms or APIs that serve as a critical dependency for a large set of engineering teams.

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.

Our team is part of the Core Machine Learning organization and focused on accelerating AI innovation across Google. This involves building the premier software stack to support the entire lifecycle for a vast array of machine learning models from genAI and LLMs to classic deep learning and large recommender systems. By solving the most critical tests of scale and efficiency, we create a single, frictionless path from research to production that empowers Google's products, differentiates Google Cloud, and fosters a global community of innovators.

The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.

We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.

The US base salary range for this full-time position is $197,000-$291,000 + 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

• Partner with Google’s various product teams to understand their most complex machine learning tests, spanning the entire machine learning (ML) lifecycle from data strategy and modeling to production deployment.
• Design and build solutions that help teams like Search, Ads, YouTube, and Waymo transition to modern AI, guiding critical new models from initial pilot to full production.
• Collaborate closely with leading AI infrastructure teams across Alphabet and Google Cloud to define and build the core frameworks and tools that will power ML development.
• Build the high-leverage platform that enables Google’s product teams to transform thousands of existing ML pipelines into genAI-based systems while maintaining business continuity and efficiency.