Research Engineer - GeminiApp Personalization

Snapshot:

We are the Gemini App team in Google DeepMind, building the next-generation AI assistant from Google. Be at the forefront of AI innovation with Gemini, featuring native multimodality, an expansive context window (up to 2 million tokens), and superior performance. Our mission is to empower billions of people by providing deeply personalised and helpful products. In this role, you will be a part of a team building a personal AI assistant that is tailored to the unique interests, passions, and curiosities of individuals.

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:

As a Research Engineer on the Gemini App Personalization team, you will build the next generation personal AI assistant on top of Google’s state-of-the-art Gemini models. Personalization is a top priority for the company, and we aim to build and launch personalized features across the Gemini App surfaces including web, mobile, and Live. We also plan to develop new personalization-related capabilities, including understanding and contextualizing relevant personal information, and using it appropriately in responses and tool invocations. The work encompasses a diverse set of tasks, including model post-training, evaluation, data retrieval and summarization, benchmark creation, data collection & synthesis, model serving, and production deployment.

Key responsibilities:

• Design, prototype, and build robust, scalable, user-facing personalization features on the full Gemini App stack.

• Perform relevant data analysis of user feedback, logs, and evaluation tasks to identify personalization-related quality issues and opportunities.

• Propose and implement targeted quality improvements via fine-tuning or prompting.

• Develop robust evaluation techniques (both automated and with a human in the loop) to assess and hill-climb on personalization quality.

• Act as primary owner and critical judge of model output quality for specific personalization features.

• Contribute to the development of a robust data flywheel, driving continuous improvement and innovation.

• Partner closely with research scientists, engineers and cross-functional partners (product and program managers) to advance the business goals of the organization.

About you:

We seek out individuals who thrive in ambiguity and who are willing to help out with whatever moves prototypes forward. We regularly need to invent novel solutions to problems, and often change course if our ideas don’t work out, so flexibility and adaptability to work on any project is a must.

In order to set you up for success as a Software Engineer at Google DeepMind, we look for the following “must have” skills and experience:

• BSc, MSc or PhD/DPhil degree in computer science or other quantitative scientific field, or similar experience working in industry,

• Solid proficiency in Python or C++,

• Deep understanding of machine learning and statistics,

• Experience with TensorFlow, JAX, PyTorch, or similar leading deep learning frameworks,

• Experience with deployment in production environments

• Experience working with LLM or ML evaluations systems,

• Solid understanding of Deep Learning fundamentals, including transformer architectures, attention mechanisms, and optimization techniques,

• Experience adapting LLMs (e.g. supervised fine-tuning, RLHF, prompt optimization),

• Experience with data pipelines and techniques for processing large-scale user data,

• Excellent communication skills and interpersonal skills.

In addition, the following “preferred skills” would be an advantage:

• Experience in empirically-driven research and development,

• Experience working on personalization for machine learning models,

• Cross functional collaboration experience,

• Prior experience collaborating with engineers, researchers, and product teams,

• Experience with user modeling techniques tailored for personalization,

• Experience building and shipping features for large-scale, user-facing products.

• Research background in NLP / Generative AI

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.

Note: In the event your application is successful and an offer of employment is made to you, any offer of employment will be conditional on the results of a background check, performed by a third party acting on our behalf. For more information on how we handle your data, please see our Applicant and Candidate Privacy Policy.

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 opportunities 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.