Research Scientist - GenAI & Multimodal LLMs

DeepMind Technologies Limited; New York (NY); On-site; USD 174,000 - 252,000; Full time

Benefits offered by this job

Equity

Bonus target

Benefits

Job summary

Google DeepMind is seeking a Research Scientist to set up large-scale tests, deploy ideas quickly and broadly, and manage deadlines and deliverables while applying the latest theories to develop new and improved products, processes, or technologies.

You will design experiments, prototype implementations, and architect new systems, working on problems spanning machine learning, data mining, natural language processing, hardware and software performance analysis, and more.

Qualifications

• PhD in Computer Science or related field.
• 2 years of experience leading a research agenda and influencing other researchers.
• 2 years of experience in an applied research setting.
• Experience in software engineering, including coding, code reviews, design discussions and reviews.
• Experience in Artificial Intelligence or Machine Learning.

Responsibilities

• Bring a combination of engineering and research expertise to advance Gemini's multimodal understanding and generation capabilities.
• Design, implement, and scale state-of-the-art Large Language Models (LLMs) core image/video understanding capabilities.
• Drive end-to-end experimental workflows across pre-training and post-training.
• Build robust, scalable infra and data pipelines to support high-quality multimodal training and eval benchmarks.
• Partner closely with Research Scientists and Software engineers (SWE) to transition cutting-edge research prototypes into production-ready foundation models, striking the right balance between rapid prototyping, maintainability, and generality.

Skills

Research leadership

AI/ML experience

Software engineering

Design discussions

Education

PhD in Computer Science or related field

Tools

GenAI techniques

LLMs

Multimodal models

Job description

Google DeepMind is seeking a Research Scientist to set up large-scale tests, deploy ideas quickly and broadly, and manage deadlines and deliverables while applying the latest theories to develop new and improved products, processes, or technologies.

You will design experiments, prototype implementations, and architect new systems, working on problems spanning machine learning, data mining, natural language processing, hardware and software performance analysis, and more.