Distinguished Engineer, Systems Research

Minimum qualifications:

• Bachelor's degree in Computer Science, Electrical Engineering or equivalent practical experience.
• 15 years of experience in software engineering research, or building and scaling systems.
• Experience developing infrastructure, solutions, or research within engineering environments.
• Experience authoring and co-authoring publications in systems research venues.

Preferred qualifications:

• PhD in Electrical Engineering, Computer Science, or related field.
• 20 years of experience in research and engineering.
• Experience leading both product and engineering, or research/applied science.
• Experience and established presence within the systems research community, with the ability to influence external thought leaders and help advocate for Google.
• Ability to quickly ramp up in new subject areas with short notice to guide mission-critical research into the largest potential risks related to Google infrastructure usage.
• Excellent communication and leadership skills to influence technical leaders across the company.

About the job

SystemsResearch@Google (SRG) is positioned in the heart of Google’s Cloud and Infrastructure engineering organization, with the mission of shaping the future of hyperscaler systems design for Google and its ecosystem. We are focused on inventing, incubating, and infusing new concepts, designs, and technologies into Google’s applications, systems, and data centers. The team’s position allows seamless engagement with Engineering and Product teams, enabling joint exploration in concert with transformative workloads. Beyond Google, the SRG team looks to forge strong relationships with external research communities working on the most pressing systems-research problems. SRG's current growth focus is to build our research depth, including Systems and the intersection of Systems and Machine Learning.

As a Distinguished Engineer, you will be responsible for developing and integrating Systems and AI research with our products while working closely with all the Infrastructure teams, Research/GDM teams, and our customers to improve adoption. You will lead a team of research talent, advising and guiding them towards execution. You will partner with Google Research, Cloud, YouTube, Search Engineering and Product teams to guide technical directions and land the technical roadmap with a research focus. You will also work with customers, Solutions Architects, Sales Leads, and GTM colleagues to understand customers' use cases, and translate them into technical designs and implementations.

The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.

We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.

The US base salary range for this full-time position is $349,000-$485,000 + 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

• Follow research trends in AI and Systems to determine the group’s research and innovation strategy.
• Build deep partnerships across Google’s product areas (e.g., GDM, Google Cloud, Research, Ads, YouTube, Devices and Services, etc.) deeply understanding their strategic data priorities and infrastructure requirements.
• Drive decisions around prioritization, solutions, functionality and optimizing for performance and cost.
• Draw other top research talent to Google and Google Cloud. 
• Develop and drive the implementation of metrics that evaluate our effectiveness in the AI and Systems space.