Prepin
Log in
Google

engineering opportunity

Senior Staff ML Software Engineer, AI Generated Content Quality, Search Discover Feed

Lead the development of advanced AI-generated content recommendation frameworks and implement quality evaluation systems for LLMs. Optimize ML inference and drive end-to-end modeling for personalization to improve performance across global surfaces.

Mountain View, California, United StatesonsiteFULL_TIME

Posted

About the role

What will you do at Google?

MINIMUM QUALIFICATIONS:

* Bachelor's degree in Computer Science, a related technical field, or

equivalent practical experience.

* 8 years of experience in software development.

* 7 years of experience leading technical project strategy, ML design, and

working with industry-scale ML infrastructure (e.g., model deployment, model

evaluation, data processing, debugging, fine tuning).

* Experience building quality evaluation frameworks for large language models.

* Experience building and deploying recommendation systems models (retrieval,

prediction, ranking, personalization, search quality, embedding) in

production.

PREFERRED QUALIFICATIONS:

* Master’s degree or PhD in Engineering, Computer Science, or a related

technical field.

* 5 years of experience in a technical leadership role leading project teams

and setting technical direction.

* Experience building advanced offline and online quality evaluation frameworks

for Large Language Models (LLMs).

* Experience integrating advanced quality evaluation frameworks with downstream

recommendation signals.

* Experience mentoring executive engineers and influencing broader

organizational machine learning strategies.

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 team leverages AI-generated content across major surfaces, ensuring optimal

user experience at a massive scale.

In this role, you will

  • focus on end-to-end
  • personalization and system optimization, integrating feedback loop signals to
  • enhance model performance for over 4 billion users.
  • In Google Search, we're reimagining what it means to search for information –
  • any way and anywhere. To do that, we need to solve complex engineering
  • challenges and expand our infrastructure, while maintaining a universally
  • accessible and useful experience that people around the world rely on. In
  • joining the Search team, you'll have an opportunity to make an impact on
  • billions of people globally.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
  • [https://www.google.com/about/careers/applications/benefits/].
  • RESPONSIBILITIES:
  • * Lead the development of advanced AI-generated content (AIGC) recommendation
  • frameworks and agentic flows to generate high-quality content for Discover
  • and Notifications.
  • * Build and implement advanced offline and online quality evaluation frameworks
  • for LLMs to ensure content factuality, freshness, and coherence.
  • * Conduct advanced quality evaluations and leverage dense recommendation
  • signals and feedback to improve the overall performance of the AIGC stack.
  • * Drive end-to-end modeling for the personalization flow, focusing heavily on
  • inventory quality, retrieval, ranking, user understanding, and budgeting
  • predictions.
  • * Optimize ML inference and resolve system-level bottlenecks to improve serving
  • efficiency for low-latency, high queries-per-second (QPS) global surfaces.

Which skills does this role require?

Software DevelopmentRecommendation SystemsData ProcessingModel EvaluationModel DeploymentInference OptimizationRankingPersonalizationEmbeddingSoftware EngineeringAI-Generated ContentSearch QualityFeedback LoopsLatency OptimizationAgentic FlowsInfrastructureGoogle SearchDiscover FeedNotificationsFull-stackFactualityFreshnessCoherenceInventory QualityBudgeting PredictionsServing Efficiency

Make your next move

Build a shortlist and prepare

Identify the requirements you can demonstrate, then choose examples from your work to discuss with the hiring team.

Review the responsibilities and requirements before adding an opening to your shortlist.

Role information can change. Confirm current details on the original application page.

Product

AI Candidate AgentCompaniesBrowse JobsDeep ProfileSkill AssessmentOpportunity Matching
Prepin.ai

© 2026 Prepin | All rights reserved.