Senior Research Engineer - GeminiApp Personalization, Mountain View

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.

• 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.

• 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.