Google is seeking a Staff Research Engineer with expertise in Applied Machine Learning (ML) to join our Applied ML team in London. In this role, you will be at the forefront of developing cutting-edge ML technologies, translating emerging research into practical, scalable solutions that can impact Google’s global user base. You’ll collaborate with top-tier researchers and engineers from Google Research and DeepMind to drive innovation and implement transformative ML solutions across various Google products.This is an excellent opportunity for a highly skilled engineer or researcher to build and lead a team, design innovative ML systems, and directly contribute to the future of AI at Google. Your work will shape the future of machine learning, from natural language processing (NLP) to computer vision and generative AI, impacting millions of users and businesses worldwide.

Responsibilities

• Build and lead a new team of ML engineers and researchers based in London, fostering a positive, inclusive, and high-performing team culture.
• Collaborate with Google Research and DeepMind to identify key research areas and translate emerging ML research into impactful, production-ready solutions across Google products.
• Conduct applied research in areas such as parameter-efficient tuning, multimodal modeling, media generation, Large Language Models (LLMs), and recommender systems.
• Develop, evaluate, and scale ML models for critical pilot projects, ensuring they meet production standards and are ready for large-scale deployment.
• Develop a strategic roadmap for the applied ML team, driving the adoption of new technologies and frameworks across Google products and services.
• Work closely with product teams to understand business needs and deliver innovative solutions, advancing ML capabilities at the intersection of research and production.

Minimum Qualifications

• Bachelor's degree in a technical field, or equivalent practical experience.
• 8+ years of experience in software development and working with data structures/algorithms.
• 5+ years of experience building and architecting large-scale, production-quality ML systems.
• 5+ years of experience in distributed development and large-scale data processing.
• Proficiency in C++ or Python.
• Strong foundation in ML fundamentals, including supervised, unsupervised, and reinforcement learning.
• Experience with natural language processing (NLP), computer vision, and generative AI techniques.

Preferred Qualifications

• Experience with generative models (e.g., diffusion models, GANs, transformers) for different media formats (text, image, video, audio), including prompt engineering, fine-tuning, and evaluation.
• Familiarity with reinforcement learning (RL) algorithms and frameworks (e.g., policy gradient methods, Q-learning, actor-critic architectures).
• Proven ability to lead and build high-performing research or engineering teams, fostering a positive, inclusive culture.
• A track record of publications in ML/AI conferences or journals, showcasing a strong research background and ability to communicate complex technical concepts effectively.
• Experience with agent-based architectures, tool use, and techniques for evaluating and optimizing agent behavior.

About Google and the Applied ML Team. Google’s software engineers and researchers work on the next-generation technologies that change how billions of users interact with information. The Domain Applied ML team is a crucial part of the Core ML organization, driving the adoption of advanced AI technologies across various Google products. By leveraging the latest research, the team develops efficient ML solutions in domains like multimodal modeling, LLMs, media generation, and more.

Why Google?
Google is proud to be an equal opportunity employer, welcoming applicants regardless of race, gender identity, sexual orientation, disability, or veteran status. We also offer reasonable accommodations for applicants with disabilities during the application process.