Staff Software Engineer, Vertex GenAI Evaluation Service

Operate as a technical expert and leader within the Cloud AI Quality Evaluation team.Drive high-quality, scalable evaluation frameworks and tools for GenAI developers and lead features to enable seamless developer experience in each stage of GenAI evaluation.Develop and implement strategies for evaluation solutions to measure model and agent quality performance at scale, design infrastructure and product features of the evaluation frameworks to evaluate advanced agent features. Collaborate with model and agent quality teams, develop scalable systems, and ensure our evaluation workflow is efficient and provides high quality user experience.Engage with customers, investigate and understand product usability gaps, customer pain points, and lead GenAI research.Minimum qualifications:Bachelor's degree or equivalent practical experience. 8 years of experience in software development.5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).2 years of experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (e.g., language modeling, computer vision).Preferred qualifications:Master’s degree or PhD in Engineering, Computer Science, or a related technical field. 5 years of experience with LLM evaluation, machine learning algorithms and tools, and general generative AI development.3 years of experience working in a complex organization involving cross-functional, or cross-business projects.Experience building and maintaining scalable production systems.Knowledge on enterprise control planes and security horizontals.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.With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.In this role, you will be working with a team of engineers, machine learning experts, etc. in advancing artificial intelligence. The Cloud AI Quality Evaluation team defines success and builds evaluation and optimization harness for Cloud AI LLM products, establishes AutoEval metrics to track quality, and provides clear insights to guide development. We work closely with Google DeepMind Research teams to advance LLM evaluation and bring SOTA evaluation technology to Cloud. As a Staff Software Engineer on this team, you will be at the forefront of building solutions for the model and agent evaluation framework and optimization tools.Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $207000 - $301000 (USD) + 20% bonus target + equity + benefitsLearn more about benefits at Google.Bachelor's degree or equivalent practical experience. 8 years of experience in software development.5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).2 years of experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (e.g., language modeling, computer vision).