Senior Research Scientist, Gemini Omni, DeepMind

Google DeepMind; San Francisco (CA); On-site; USD 174,000 - 252,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

Google DeepMind in San Francisco is seeking a senior research scientist to lead foundational work in generative AI and multimodal models for billions of users. You will shape research directions, collaborate with interdisciplinary teams, and publish and present findings.

The role offers competitive compensation with annual bonus target and equity, plus benefits and opportunities for career growth within a leading AI lab.

Qualifications

• PhD in Computer Science, related field, or equivalent practical experience.

Responsibilities

• Drive foundational research in next-generation generative modeling to pioneer multimodal generation across image, video, and audio.
• Formulate novel methodologies and perform literature reviews to solve open-ended AI challenges with independent judgment.
• Pioneer model optimization and efficient inference strategies to reduce compute overhead and scale multimodal systems.
• Advance learning-based alignment with reinforcement learning to enhance model reasoning and generation quality.
• Apply rigorous engineering practices to design robust benchmarks and validate real-world impact of findings.

Skills

JAX/PyTorch/TensorFlow experience

GenAI techniques knowledge

ML algorithms expertise

Research leadership

Academic ML research experience

Job description

Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.

Minimum qualifications

• PhD in Computer Science, a related field, or equivalent practical experience.
• 3 years of experience in development with JAX, PyTorch, or TensorFlow.
• 3 years of experience with machine learning and machine learning algorithms.
• 3 years of experience with Generative Artificial Intelligence (GenAI) techniques (e.g., Large Language Models, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
• 2 years of experience leading a research agenda.
• Experience in academic research within machine learning, publications, or research in related fields.

Preferred qualifications

• 2 years of coding experience.
• 1 year of experience leading research efforts and influencing other researchers.

About The Job

We research and develop machine learning models for billions of Google users. 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 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: $174000 - $252000 (USD) + 15% bonus target + equity + benefits

Responsibilities

Learn more about benefits at Google.

• Drive foundational research in next-generation generative modeling (e.g., autoregressive architectures, diffusion models) to pioneer breakthroughs across multimodal generation, including image, video, and audio synthesis.
• Formulate novel scientific methodologies and conduct deep literature reviews to solve complex, open-ended AI challenges, exercising independent judgment to balance immediate project milestones with long-term frontier research.
• Pioneer model optimization and efficient inference strategies to significantly reduce compute overhead, optimize latency, and scale large multimodal systems across high-performance infrastructure.
• Advance post-training and capability scaling using reinforcement learning to enhance model alignment, reasoning, and multi-turn generation quality across modalities.
• Apply rigorous engineering and experimental practices to design robust benchmarks, measure real-world performance, and systematically validate the scientific and practical impact of research findings.

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.