Research Engineer, Gemini Personalization

About the position

We are the Gemini App team in Google DeepMind, building the everyday 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 with deeply personalised and helpful products, delivering an experience users love. In this role you will be a part of a team building a personal AI assistant. One that doesn’t just answer general questions, but understands you — tailoring its help to your specific interests, passions, and curiosities.

Responsibilities

• Play a key role in building the state-of-the-art personalized AI assistant on Gemini.
• Conduct personalization research encompassing model innovation, post-training refinement, advanced evaluation, benchmark creation, data generation, and scalable deployment.
• Improve the model’s ability to reason about user information.
• Create robust evaluation frameworks to measure personalization quality.
• Build scalable systems to deliver tailored experiences to a wide user base.
• Engage in continuous experimentation and refinement to push the boundaries of personalization in AI.

Requirements

• BSc, MSc or PhD/DPhil degree in computer science, mathematics, applied stats, machine learning or similar experience working in industry.
• Proven knowledge and experience of Python or C++.
• Deep understanding of machine learning and statistics.
• Strong knowledge of algorithm design and data structures.
• Proven experience with TensorFlow, JAX, PyTorch, or similar leading deep learning frameworks.
• Recent experience conducting applied research to improve the quality and training/serving efficiency of large transformer-based models.
• Experience fine-tuning and adaptation of LLMs (e.g. supervised fine-tuning, RLHF).
• Experience applying and productionizing state-of-the-art large visual, language and multimodal research into real-world applications.
• Experience with user modeling techniques tailored for personalization.
• Understanding of personalization metrics and evaluation challenges (e.g., relevance, diversity, novelty, serendipity, offline vs. online evaluation).
• Solid understanding of Deep Learning fundamentals, including transformer architectures, attention mechanisms, and optimization techniques.
• Software Engineering experience and experience working on large-scale ML projects highly desirable.
• Experience with data pipelines and techniques for managing, processing, and utilizing large-scale user data while adhering to privacy best practices.
• Ability to design and analyze rigorous offline and online (A/B) experiments to validate personalization improvements.
• Proven experience working in industry, working on projects from proof-of-concept through to implementation highly beneficial.
• A passion for Artificial Intelligence.
• Excellent communication skills and proven interpersonal skills, with a track record of effective collaboration with cross-functional teams.

Nice-to-haves

• Experience in applying experimental ideas to applied problems.
• Cross functional collaboration experience.
• Prior experience collaborating with researchers.
• Prior experience working with product teams.

Benefits

• Base salary range between $166,000 - $244,000 + bonus + equity + benefits.