Vision AI Research Scientist — Multimodal LLMs

Google DeepMind; Los Angeles (CA); On-site; USD 207,000 - 300,000; Full time

Job summary

Google DeepMind in Los Angeles, CA (US) invites applications for a Research Scientist role. The job spans large-scale LLM and multimodal research, with duties from designing experiments to deploying ideas broadly across products and platforms.

You will publish findings, collaborate with international academic partners, and contribute to safe, ethical AI while advancing core AI/ML techniques and infrastructures. Expected compensation is substantial with equity and benefits.

Qualifications

• 3 years of experience in software engineering or related technical field.
• 2 years of work experience in an applied research setting.
• Experience in Artificial Intelligence or Machine Learning.
• Experience developing autonomous agents, multi-agent workflows, or agentic frameworks; and experience designing, pre-training, fine-tuning, or evaluating LLMs and multimodal models.
• Contributions to research communities with publications at major conferences (authors).

Responsibilities

• Design, implement, and scale state-of-the-art LLMs core image/video understanding.
• Drive end-to-end experimental workflows across pre-training and post-training.
• Build robust, scalable infra and data pipelines for multimodal training and evals.
• Collaborate with Research Scientists and SWEs to productionize research prototypes.
• Analyze metrics and failure modes to improve model quality.

Skills

Software eng

Applied research

AI/ML experience

Autonomous agents

Publications

Education

Master's or PhD

Tools

AutoGen

CrewAI

LangGraph

Tool-use

Job description

Google DeepMind in Los Angeles, CA (US) invites applications for a Research Scientist role. The job spans large-scale LLM and multimodal research, with duties from designing experiments to deploying ideas broadly across products and platforms.

You will publish findings, collaborate with international academic partners, and contribute to safe, ethical AI while advancing core AI/ML techniques and infrastructures. Expected compensation is substantial with equity and benefits.