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.

We are the Recommendations Machine Learning (RecML) team in Core ML's Applied ML organization. Our mission is to accelerate product innovations through ML for recommendations and user modeling. We collaborate with various Alphabet product areas and partner with them to help accelerate product innovations through applied research in recommendations and user modeling. We also generalize successful innovations into standardized, maintainable, and production-grade solutions for use by other teams and products.

The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.

We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.

The US base salary range for this full-time position is $197,000-$291,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Define and execute the applied research roadmap for the Large User Model ecosystem, balancing immediate customer needs with long-term technical evolution to scale foundational models across high-traffic surfaces.

• Support initiatives with product leadership to translate complex business goals into technical model formulations, delivering step-function improvements in user engagement and business metrics while optimizing for latency and performance trade-offs.

• Optimize model performance by researching and implementing adaptation techniques (transfer learning/domain adaptation) that balances high-quality output with strict inference latency requirements for production environments.

• Drive architectural improvements by establishing a strategic feedback loop with pre-training teams, utilizing downstream performance analysis to influence data curation, model architecture, and novel evaluation metrics for engagement-specific needs.

• Design and productionize fine-tuning pipelines that translate general-purpose state-of-the-art (SoTA) Foundation User Models into effective, domain-specific recommendation engines.

Minimum qualifications

• Bachelor’s degree or equivalent practical experience.

• 8 years of experience in software development.

• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.

• 5 years of experience with ML design (e.g., model deployment, model evaluation, data processing, debugging, fine-tuning).

• Experience with Transformer-based models (e.g., BERT, T5, GPT, ViT), with a focus on attention mechanisms and architecture variations.

Preferred qualifications

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.

• 8 years of experience with data structures/algorithms.

• 3 years of experience in a technical leadership role leading project teams and setting technical direction.

• 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.

• Experience of publishing in venues or contributing to open-source projects related to Rec Sys, transfer learning, NLP/CV, or multimodal systems.

• Understanding of modern recommendation architectures (e.g., two-tower models, sequential user modeling) and how to integrate Large Foundation Models into existing ranking/retrieval stacks.