Requirements:

Bachelor's degree or equivalent practical experience.
8 years of experience in applied machine learning, including leading projects from research to production.
Experience building and leading engineering or research teams.
Experience in Python and ML frameworks like JAX, TensorFlow, or PyTorch.
One or more publications in top-tier ML/AI conferences or journals (e.g., NeurIPS, ICML, ICLR, CVPR).

Nice to haves:

Master's degree in Computer Science, a related technical field, or equivalent practical experience.

Act as the technical expert for a small team. Guide research directions and mentor team members through your own direct contributions.
Lead the end-to-end research process, from defining novel problems and prototyping solutions to publishing results and partnering with product teams to ship features.
Shape and execute the team's technical roadmap by collaborating with stakeholders in Google Research, DeepMind, and product areas to identify and pursue opportunities.
Utilize and advance techniques on Google's infrastructure. Your work will involve Python, JAX/TensorFlow, and focus on areas like Parameter-Efficient Tuning (PET), multimodal modeling, and agentic systems using models like Gemini.
Research and product by translating technical concepts into actionable plans and user value, while advocating research excellence through publications in conferences and open-source contributions.

The Domain Applied ML (DAML) team accelerates the adoption of AI across Google.
You will lead a new applied ML team in London, bridging the gap between research and real-world application.
Opportunity to work on emerging areas like generative AI and multi-agent systems with impact on products like Search, YouTube, and Waymo.
Work in AI and Infrastructure team, redefining what's possible and empowering Google customers with breakthrough capabilities and insights.