Research Scientist, Retrieval and Ranking

Snapshot

The mission of our team is to improve LLM's fundamental capabilities in retrieval and ranking. 

Information retrieval is central to Google. With the new generative AI experiences, it is an emerging problem to rethink how retrieval and ranking can be done and build the next-generation LLM-powered solutions.

About Us

Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.

The Role

LLMs/Gemini have demonstrated impressive capabilities, yet it is an open question whether these models can be used to efficiently solve large-scale retrieval and ranking problems that are central to the Google business. 

The goal of our team is to study and build the next-generation LLM-powered retrieval and ranking model, providing an end-to-end generative experience. 

The work will have impacts on many applications and workstreams including Ads, Search, personalization/memory and long-context modeling.

Our team has an extensive track record of building embedding and RAG style models at Google. With the new project and roles, we hope to go beyond the conventional embedding and RAG view and revolutionize how retrieval and ranking is done at Google.

Key responsibilities:

• Develop new model architecture, training and inference techniques.
• Conduct large-scale analysis and experiment. 
• Collaborate with different teams in the GenAI org and PAs and apply the techniques to real-world applications.

About You

In order to set you up for success as a Research Scientist at Google DeepMind,  we look for the following skills and experience:

• PhD in Computer Science, or Machine Learning related field.
• Demonstrated experience in data preparation, training, and evaluation of LLM models.
• A strong record of publications in top-tier machine-learning related conferences

In addition, the following would be an advantage: 

• Experience in low-level programming optimizing LLM training and inference efficiency.
• Experience in information retrieval and ranking.

The US base salary range for this full-time position is between $166,000 - $244,000 + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process.

At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.