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Job Details
Posted date: Sep 02, 2026
There have been 4 jobs posted with the title of Senior Software Engineer, AI/ML all time at Google.Location: Kirkland, WA
Level: Senior
Description
Learn new technical domains by combining a deep knowledge of Google's expansive software stack with AI-assisted research to quickly propose and implement innovative technical solutions. Build scalable AI-powered solutions horizontally across Google while delving deeply into external systems to proactively assist other teams with their most complex challenges. Help the team strategically identify game-changing problem spaces, dynamic pursuing and contributing proposals for opportunities that maximize our overall impact. Contribute to a collaborative, ambitious culture that confidently tackles the impossible and constantly questions the strict technical boundaries. Guide junior engineers and lead focused strike teams by setting clear technical direction, providing vital support to ensure both their rapid professional growth and overall outcome success.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.
This is an opportunity to participate in a fast-moving, high-impact AI-native team, and play a part in defining how Google leverages AI to deliver qualitatively different engineering outcomes compared to pre-AI ways of working.
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.
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.
Qualifications
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++, Go or Java). 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging). Experience designing, building, and maintaining infrastructure. Experience designing, developing, and deploying artificial intelligence (AI) models or machine learning algorithms.Preferred qualifications: Master's degree or PhD in Computer Science or related technical field.
5 years of experience with data structures and algorithms. Experience applying AI to solve software engineering problems, with a background or strong interest in agentic software development (LLMs, code generation, etc.). Experience in driving significant operational efficiencies (e.g., compute, storage, latency) and structural software improvements (e.g., code quality, testing speed) in production, brown-field systems. Experience designing, building, maintaining, optimizing, and debugging large-scale, high-performance distributed production systems (e.g., replicated state machines, database systems, networking, or storage).