Minimum qualifications:- Bachelor's degree or equivalent practical experience.
- 2 years of experience in software development (e.g., C , Python).
- 2 years of experience in testing, maintaining, or launching software products.
- Experience building, training, and deploying machine learning models using TensorFlow, JAX, or Adbrain.
- Experience working with ranking, retrieval and other recommendation systems models.
Preferred qualifications:- Master's degree or PhD in Computer Science or related technical fields.
- 2 years of experience with data structures and algorithms.
- Experience with generative AI techniques (e.g., LLMs, natural language processing) and integrating them into production systems.
- Excellent investigative and quantitative reasoning skills, with a foundation in statistics and experiment design (A/B testing).
- Proven track record of managing large-scale ML systems, conducting analysis of quality systems, and identifying bottlenecks to improve performance.
About the jobIn this role, you will be at the forefront of integrating highly relevant travel ads into AI Overviews/AI Mode and web search experiences. You will bridge the gap between generative AI and core ads infrastructure. You will build and optimize the deep learning models powering ads ranking and retrieval alongside integrating a Large Language Model (LLMs).
You will leverage user intent and contextual signals to deliver ads that feel like a natural, helpful extension of the user's travel planning journey. This is a unique opportunity to apply your expertise in recommendation/search system and deep learning technology (Adbrain, TensorFlow, JAX) to scale features, drive significant business impact, and shape the future of travel discovery.
US: $147000 - $211000 (USD) 15% bonus target equity benefits
Learn more about benefits at Google .
Responsibilities- Build, train, and scale deep learning models for ranking, retrieval and generation use cases using Adbrain, TensorFlow, or JAX, alongside efficient GenAI inference integration.
- Own the end-to-end design implementation, and deployment of ML features and data pipelines across AI surfaces, ensuring high code quality and system performance.
- Design, launch, and analyze A/B experiments to evaluate model performance, monitor user engagement, and drive improvements in ad relevance and business.
- Work closely with immediate teammates and cross-functional partners (Product, Data Science, UX) to clarify requirements and resolve technical blockers.
