Staff Research Engineer, LLMs and Generative Media: Google

This role is with the Domain Applied ML (DAML) team, a group within Core ML. DAML's mission is to accelerate the adoption of AI across Google by partnering with Google Research and DeepMind to translate their breakthroughs (like Gemini) into standardized, efficient solutions. The team addresses issues from initial prototyping (0-to-1) to large-scale deployment (1-to-10).

About the Role
As a Staff Research Engineer, you will lead a new applied ML team in London. You will serve as the team's technical anchor, bridging the gap between cutting-edge research from Google Research and DeepMind and its real-world application. This is a hands-on role where you will guide a small group of researchers while also dedicating significant time to your own experimentation and coding. Your work will focus on emerging areas like generative AI and multi-agent systems to deliver a measurable impact on products like Search, YouTube, and Waymo.

Responsibilities
Act as the technical expert for a small team, guiding research directions and mentoring members through your own direct contributions.

Lead the end-to-end research process, from defining novel problems and prototyping solutions to publishing results and shipping features with product teams.

Shape and execute the team's technical roadmap by collaborating with stakeholders in Google Research, DeepMind, and various product areas.

Utilize and advance techniques on Google's infrastructure, working with Python, JAX/TensorFlow, and focusing on areas like Parameter-Efficient Tuning (PET), multimodal modeling, and agentic systems using models like Gemini.

Translate technical concepts into actionable plans and user value, while advocating for research excellence through publications and open-source contributions.

Requirements
Minimum Qualifications:

A 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).

Preferred Qualifications:

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