Research Scientist, Multimodal Alignment, Safety and Fairness, DeepMind

Google•Kirkland, WA

7d•$147,000 - $210,000

About The Position

Google DeepMind is a pioneering AI lab whose interdisciplinary teams advance AI to address complex global challenges and accelerate product innovation. The organization emphasizes widespread public benefit and scientific discovery, with safety and ethics as top priorities. Research Scientists develop new and improved products, processes, and technologies by applying current theories to real-world computer science problems. The work can include setting up large-scale tests, deploying promising ideas, creating experiments and prototypes, and designing architectures. Researchers contribute to the wider research community by sharing and publishing findings, drawing on internal projects and collaborations with universities and technical institutes. The role supports a range of research emphases and career pathways, with work carried out through collective effort. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. The stated U.S. compensation is $147,000–$210,000, plus a 15% bonus target, equity, and benefits.

Requirements

PhD in Computer Science, Machine Learning, or a related technical field, or equivalent practical experience.
Experience in Python and deep learning frameworks such as JAX, Flax, or Gemma.
Experience developing multimodal AI models and systems.
Experience conducting research and development, including experimental design, implementation, and analysis.
Publication record in machine learning conferences such as NeurIPS, CVPR, ICML, ICLR, ICCV, or ECCV.

Nice To Haves

Experience fine-tuning and post-training large language models using reinforcement learning or other alignment methods.
Experience developing generative AI architectures, techniques, and agentic AI solutions.
Experience with multimodal learning that integrates information from different data types, such as vision, audio, and text.
Proven expertise working with, tuning, and prototyping large-scale vision-language models using modern prompting strategies.
Strong interest in and awareness of AI alignment, safety, responsibility, and fairness, and excitement to collaborate across disciplines.

Responsibilities

Generate new ideas, keep up with the state of the art, and discuss research directions with other researchers.
Design, rapidly implement, and evaluate ideas, methods, interfaces, and tools to explore new sociotechnical AI systems.
Report and present research findings and developments clearly and efficiently, internally and externally, verbally and in writing.
Suggest and engage in inter- and intra-team collaborations to meet ambitious research goals while driving significant individual contributions.
Take ownership of substantial technical projects from ideation and design through implementation and evaluation, often involving cross-functional collaboration.
Set up large-scale tests and deploy promising ideas quickly and broadly while managing deadlines and deliverables.
Contribute to the wider research community by sharing and publishing findings.