Senior Software Engineer, Operations Research and Gemini

Senior Software Engineer, Operations Research and Gemini

Google

Zürich, Switzerland

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 PhD 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

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.

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.