Research Engineer, Serving Quality, DeepMind

Research Engineer, Serving Quality, Deep Mind

Deep Mind Mountain View, CA, USA

• Bachelor's degree in Computer Science, Mathematics, Statistics, Machine Learning, a related field, or equivalent practical experience.
• Experience with Python or C++.
• Experience with machine learning and statistics.

• Experience in software engineering and working on large-scale ML projects.
• Experience working on projects from proof-of-concept through to implementation.
• Experience in experiment analysis.
• Experience with Tensor Flow or similar ML frameworks (e.g. JAX).
• Experience conducting applied research to improve the quality and training/serving efficiency of large transformer-based models.
• Familiarity with LE and Rasta.

In this role, you will work cross-functionally with researchers, engineers and operations on live experiment set up, user and model behavior analysis, and metrics improvements to ensure that we have the best quality of data for GenAI model and product developments. This role also works with the modeling teams closely to provide user signals feedback and insights on improving our frontier models.

Artificial intelligence will be one of humanity’s most transformative inventions. At Google Deep Mind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.

We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google .

• Design and develop metrics that measure model performance, and detect anomaly events on serving stack (such looping, leakage and so on).
• Discover novel serving or modeling quality issues, as well as anomaly events through large-scale real user data mining.
• Work cross-functionally on logging, serving, and management to quantify the improvements.
• Contribute to reporting, analytical infrastructure, model testing framework including replay, evals and dashboarding.
• Provide insights to improve our frontier models serving quality and improve user experiences.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law.

See also Google's EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire .

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc.

stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.