Gemini Vision Research Scientist, DeepMind

Google LLC; Mountain View (CA); On-site; USD 207,000 - 300,000; Full time

Benefits offered by this job

Equity

Bonus target

Benefits

Job summary

Google LLC in Mountain View seeks a Research Scientist to design, implement, and scale state-of-the-art LLMs for multimodal understanding. You will run large-scale experiments, prototype architectures, and collaboratively push research ideas toward production-ready foundations that impact real-world products and platforms.

The role emphasizes independent data generation, model training, and optimization pipelines, with opportunities to publish and contribute to the wider research community

Qualifications

• 3 years of 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 designing/evaluating LLMs and multimodal models.
• Contributions to research communities or publications at conferences (NIPS/ICML/ACL/CVPR).

Responsibilities

• Design, implement, and scale state-of-the-art 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 for multimodal training and eval benchmarks.
• Partner with Research Scientists and SWEs to transition research into production-ready foundation models.
• Analyze experiment metrics and failure modes to identify opportunities for model quality improvement.

Skills

Software engineering

Applied research

AI/ML experience

Autonomous agents

LLMs & multimodal models

Publications

Education

Master's degree in CS/AI/ML

PhD preferred

Job description

Minimum 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 (e.g., AutoGen, CrewAI, LangGraph, tool-use/function-calling, or multi-agent RL); and experience designing, pre-training, fine-tuning, or evaluating Large Language Models (LLMs) and multimodal foundation models.
• Contribution to research communities or efforts, including publishing papers (being listed as author) at conferences such as NIPS, ICML, ACL, CVPR, etc.

Preferred qualifications:

• Master's degree or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, or related technical field.
• Demonstrated ability to independently manage data generation, model training, and optimization pipelines.

About the job

As an organization, Google maintains a portfolio of research projects driven by fundamental research, new product innovation, product contribution and infrastructure goals, while providing individuals and teams the freedom to emphasize specific types of work. As a Research Scientist, you'll setup large-scale tests and deploy promising ideas quickly and broadly, managing deadlines and deliverables while applying the latest theories to develop new and improved products, processes, or technologies. From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real-world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more. As a Research Scientist, you'll also actively contribute to the wider research community by sharing and publishing your findings, with ideas inspired by internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world. Artificial intelligence will be one of humanity's most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority. We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google .

Responsibilities

• Design, implement, and scale state-of-the-art LLM's 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 SWEs to transition cutting-edge research prototypes into production-ready foundation models, striking the right balance between rapid prototyping, maintainability, and generality.
• Analyze complex experiment metrics and failure modes across multimodal benchmarks to identify opportunities for model quality hillclimbing.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .