Google

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; San Francisco, CA, USA; Sunnyvale, CA, USA.

Minimum qualifications:

• Bachelor's degree in Computer Science, Mathematics, other relevant Engineering field, or equivalent practical experience.
• 15 years of experience as a Software Engineering leader in ML Infrastructure, ML or AI for products, or related fields.
• Experience with machine learning frameworks and Google serving systems or indexing systems, and with developing technical strategy to support growth of the team, function, and customers.
• Experience with large-scale machine learning systems.

Preferred qualifications:

• 15 years of experience effectively leading, growing, and scaling technical teams.
• Experience motivating others at all levels by creating a vision.
• Experience building ML infrastructure or products with heavy use of AI/ML and large groups of stakeholders or users.
• Experience in large language model, media generation, or other generative AI tuning and optimization techniques.
• Experience with working with stakeholders to understand their needs and translate them into technical requirements.
• Outstanding communication skills tailored to both technical and non-technical audiences.

About the Job

Google is a leading ML/AI company. Google’s Core ML team aims to build the state-of-the-art AI platforms, services, and tools behind Google’s AI research and AI-powered products. We are owners of the Google AI framework (e.g., TensorFlow, JAX), AI performance and efficiency, AI training and inference platforms, AI compilers (e.g. XLA), AI software/hardware co-design (e.g. TPU), and AI developer experience (e.g., Model Hub, Eval Hub). We are the driver to launch LMs (large models, like Gemini) from research to production and enable all Google products to adopt LMs to improve end-user experiences. The Core ML team is responsible for planning and optimizing ML capacity for all Google products and driving performance and efficiency work to maximize ROI for our AI investments. We look across Google’s AI efforts 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. As a Principal Engineer, you'll drive the technical strategy for orchestration of actions on top of GenAI models (and other AI models) that serve in our production serving system. This team delivers components for pre/post-processing, RAI and safety, recitation, and sequencing of actions in our GenAI products from single model request calls to agent level orchestration that are available to all of Google. This system is in a critical path for all our GenAI launches.

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.

The US base salary range for this full-time position is $294,000-$414,000 + 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

• Define the long-term strategic vision for LM Root and Recitation technology and roadmap. Establish technical direction, goals, and development priorities including rethinking the strategy to meet the needs of the future.
• Forge strong partnerships with Research, Product, Hardware, and Core ML teams. Drive alignment and effective collaboration to ensure optimal solutions for Google's custom ML strategies.
• Deliver key infrastructure in GenAI applications for products and APIs that provides both essential functionality for high quality results, helps unify our stacks across Google, and supports safety and legal requirements at serving time.
• Apply your deep expertise in Serving and Indexing systems and machine learning to optimize system performance, reduce software overheads, and seamlessly support new hardware. Advocate innovation and the application of new technologies.