Senior Software Engineer, Operations Research and Gemini

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with software development in Python.
• 3 years of experience building training and evaluation datasets for Generative AI models.
• 3 years of experience operating within the core technology stack of modern Large Language Models (LLMs).
• 3 years of experience in machine learning research or machine learning infrastructure.

Minimum qualifications

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with software development in Python.
• 3 years of experience building training and evaluation datasets for Generative AI models.
• 3 years of experience operating within the core technology stack of modern Large Language Models (LLMs).
• 3 years of experience in machine learning research or machine learning infrastructure.

Preferred qualifications

• Master's degree or Ph D in Computer Science, or a related technical field.
• 5 years of experience with data structures and algorithms.
• 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
• Experience in combinatorial optimization or other areas of operations research.
• Experience in reinforcement learning.

About The Job

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.

The Operations Research group builds technology to solve optimization problems for the world, Alphabet, and Google.

You will join a team that works at the intersection of Operations Research and Gemini, primarily focused on using optimization techniques to improve Gemini.

You will either already have a working knowledge of optimization techniques.

Google Research addresses challenges that define the technology of today and tomorrow.

From conducting fundamental research to influencing product development, our research teams have the opportunity to impact technology used by billions of people every day.

Our teams aspire to make discoveries that impact everyone, and core to our approach is sharing our research and tools to fuel progress in the field -- we publish regularly in academic journals, release projects as open source, and apply research to Google products.

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 Google's EEO Policy and EEO is the Law.

If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .

Responsibilities

• Build evaluation datasets, autoraters, and reward functions to assess and improve Gemini capabilities.
• Develop user simulators to test and refine model interactions.
• Construct agentic harnesses that enable models to interface with optimization solvers.
• Partner with product areas to integrate optimization solvers into their Generative AI offerings.
• Identify model capability gaps and devise concrete technical solutions.
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