Job Description

Minimum qualifications: + PhD in Computer Science, similar field, or equivalent practical experience. + 15 years of software engineering experience, building and working with systems in the technology organization. + 10 years of experience in applying AI solutions and ML-related technologies to solve real-world AI/ML problems in consumer or enterprise applications. + Experience with tuning Large Language Models and ML modeling. Preferred qualifications: + Experience in Large Model research and technologies. + Technical expertise in deep learning. + Experience with inter-team/cross-functional leadership. + Vigilant about technical trends, adapting quickly to new AI/ML technologies, and applying consumer or enterprise applications. Within Cloud AI, we focus on building highly differentiated, highly scalable, and easy-to-use machine learning products and services that enable our customers to transform their business with AI. Products such as Vertex, AutoML, TPU, and TensorFlow Enterprise comprise a portfolio that spans the needs of Data Scientists, Developers, and overall Infrastructure. We provide customers with state-of-the-art ML models and full ML model building/serving toolsets and management workflows. As a Principal Engineer, you will be responsible for driving, deciding, and landing the technical roadmap for our Cloud AI large model platform. You will partner with Vertex platform engineering and product teams, and work with engineering managers to guide technical direction. You'll partner closely with various partner teams both within the product (e.g., Cloud DA, Cloud GKE) and cross-product partner teams (e.g., CoreML, RMI) on collaborations. In addition, you will work with customers, solutions architects, sales leads, and GTM colleagues to understand customers' use cases, and translate them into technical designs and implementations. A significant aspect of this Principal Engineer role involves a close partnership with Google DeepMind, specifically focusing on the critical phases of post-training and large model productization within our Cloud AI offerings. You will be at the forefront of collaborating on strategies and implementations to optimize and scale DeepMind's advanced models for seamless integration into our products. This includes working on techniques for efficient deployment, inference optimization, and ensuring the reliability and performance of these large models in a production environment. Your contributions will directly impact how research translates into tangible and impactful AI solutions for our customers. 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 ( . + Define the technical roadmap for productionizing large models to Vertex and providing developer tuning tools to support Google Cloud Platform (GCP) customers tailoring large models to their business use cases. + Partner with the Google Deepmind team to drive large model innovations, and bring SOTA large model technologies to the platform. + Consult on OKRs across platform teams, review designs, participate in and help to resolve technical discussions, and drive high quality extensible engineering investments for large models. + Develop a structure of other technical leads in the area, both by defining technical goals and orienting teams around technical decisions they can make, and by providing development support to engineers in the area. + Provide leadership in a firefighting, Code Yellow, or high priority situation. Act as a technical lead or execution supervisor for high-priority, complex, or cross-functional projects. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also and If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form:

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