Senior Software Engineer, Sequence Storage Software Engineering

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.

The Sequence Storage team builds and operates an exabyte-scale managed storage solution designed for AI/ML research. Our system is a critical storage platform for DeepMind and other research teams, enabling the ingestion, processing, querying, and analysis of massive datasets (over 2 EiB and growing). We empower researchers across the entire lifecycle of AI models, underpinning their pre-training, evaluation, and post-training workflows. Crucially, we support centralized, large-scale training efforts for the next generation of Gemini models, often utilizing TPUs, directly accelerating the development and deployment of AI innovations impacting Google users.

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.

Responsibilities

• Lead the design, development, and implementation of scalable, reliable, and efficient features for the Sequence Storage core infrastructure.
• Drive projects focused on enhancing storage efficiency, spatial flexibility, and system scalability and reliability.
• Conduct performance profiling, identify bottlenecks, and implement optimizations to ensure the system is fast, cost-effective, and can manage extreme scale.
• Collaborate closely with AI/ML researchers to understand their evolving needs, translating complex requirements into robust, high-impact engineering solutions.
• Participate in the production oncall rotation, ensuring the highest standards of service reliability and availability.

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 5 years of experience programming in C++.
• 3 years of experience developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage or hardware architecture.
• Experience with Google Cloud Infrastructure's compute, storage, and networking services.
• Experience querying and managing datasets using SQL.

Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical field.
• 1 year of experience in a technical leadership role.
• Familiarity with AI/ML workflows, data pipelines, and the specific requirements of large model training.