Senior Engineering Lead, Foundational Modeling
Confirmed on the employer's own hiring board on Sep 26, 2026. First seen by Alion on Aug 25, 2026. Google scores B on the Alion truth index.
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.
With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.
We build and deploy AI to show high quality ads that power the free internet for everyone. We adapt and post-train Gemini models to improve the quality of Google Ads in modern GenAI experiences. This includes automated prompt optimization and post-training of Gemini models using SFT and RL.
Our goal is to deliver the optimal balance between monetization and user satisfaction across Search, Assistant, and Gemini surfaces by strategically selecting and presenting relevant ads.
In this role, you will lead design and implementation of an Ads-specific post-trained Gemini foundational model, and work closely with researchers and partner teams to achieve quality, performance and velocity goals.
Google Ads is helping power the open internet with the best technology that connects and creates value for people, publishers, advertisers, and Google. We’re made up of multiple teams, building Google’s Advertising products including search, display, shopping, travel and video advertising, as well as analytics. Our teams create trusted experiences between people and businesses with useful ads. We help grow businesses of all sizes from small businesses, to large brands, to YouTube creators, with effective advertiser tools that deliver measurable results. We also enable Google to engage with customers at scale.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $262000 - $364000 (USD) + 25% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Lead development of an Ads specific Gemini foundation model by post-training on multiple Ads tasks using RL and SFT (e.g., user and ad intent classification, cross-surface commercial understanding, etc).
- Architect and build a standardized framework to enable scaling of many tasks, standardized evals, experimentation, and overall velocity.
- Drive key deliverables and iterations toward major milestones (e.g., model training, benchmarks, product experimentation, launches).
- Collaborate closely with cross-functional partners across Retrieval, Targeting, Relevance (and other aspects of the Ads Prediction Stack), as well as UX.
- Drive high code and engineering hygiene, at Google-scale latency, privacy, and safety standards.
Qualifications
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience programming in Python or C++.
- 7 years of experience leading technical project strategy, ML design, and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- 5 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
- 5 years of experience with design and architecture; and testing/launching software products.
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 8 years of experience with data structures and algorithms.
- 5 years of experience in a technical leadership role leading project teams and setting technical direction.
- 3 years of experience working in an organization involving cross-functional, or cross-business projects.
- Demonstrated experience in software engineering at L7+ level, building complex distributed systems, ML pipelines, or user-facing product frameworks.
- Deep familiarity with Search/Ads infrastructure, auction mechanics, or generative AI models.