Research Scientist/Engineer, GenMedia Safety Post-Training TLM, DeepMind

Google DeepMind; Mountain View (CA); On-site; USD 262,000 - 364,000; Full time

Job summary

Google DeepMind is a pioneering AI lab whose interdisciplinary teams push the boundaries of safe and impactful AI for billions of users. We are seeking a Senior Research Manager to lead research strategy in safety, alignment, and ML across LLMs, RL, and multimodal models, while guiding a team of researchers and engineers.

This role focuses on translating scientific advances into responsible product-scale solutions and shaping the frontier of AI safety.

Qualifications

• PhD or equivalent practical research experience.
• 5 years of technical leadership experience setting direction and guiding project workstreams.
• 5 years in people management, supervision, or team leadership.
• 5 years in ML, specializing in LLMs, multimodal models, or RL with safety/alignment.
• At least one peer‑reviewed publication or public preprint.

Responsibilities

• Define architectural strategy for safety interventions across multimodal foundation models.
• Advance post-training methods across media types to ensure alignment with new prompting capabilities.
• Shape intrinsic model behavior to refuse severe harms while delivering high-quality, controllable outputs.
• Partner with cross-functional teams to translate serving-time classifiers into training rewards and expand the safety and quality frontier.
• Manage a team of 10+ researchers and engineers, modeling scientific excellence and building a collaborative culture.

Skills

Technical leadership

Machine learning

LLMs

Reinforcement learning

Safety & alignment

Education

PhD or equivalent

Job description

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; New York, NY, USA.

Minimum qualifications

• PhD or equivalent practical research experience.
• 5 years of experience in a technical leadership role setting direction and guiding project workstreams.
• 5 years of experience in a people management, supervision, or team leadership role.
• 5 years of experience in machine learning, specifically working with large language models (LLMs), multimodal foundation models, or reinforcement learning (RL), along with safety and alignment specialization (e.g., model alignment, AI safety, or post-training techniques like Supervised Fine-Tuning and reward modeling).
• One or more peer-reviewed scientific publications (e.g., NeurIPS, ICML, ICLR, CVPR, ACL, CoRL) or public preprints (arXiv).

Preferred qualifications

• 6 years of demonstrated experience initiating, scoping, and executing independent research agendas or leading collaborative academic projects.
• Experience in core strategic focus areas: LLMs, post training, reasoning and reinforcement learning, agents, multimodal perception/vision, robotics, audio/speech, safety and alignment or scientific AI (health, materials, fusion).
• Track record of bridging research breakthroughs with product engineering or external scientific/policy stakeholders.
• Sustained record of first author and senior author scientific publications in premier peer-reviewed conferences (e.g., NeurIPS, ICML, ICLR, CVPR, SIGGRAPH, CoRL) or journals (e.g., Science, Nature, PNAS).

About the job

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.

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: $262000 - $364000 (USD) + 25% bonus target + equity + benefits

Responsibilities

Learn more about benefits at Google.

• Define the architectural strategy for placing safety interventions across multimodal foundation models, balancing shared approaches with bespoke solutions.
• Advance generalizable post-training methods across media types to ensure seamless alignment as new prompting and conditioning capabilities emerge.
• Shape intrinsic model behavior to refuse severe harms while fulfilling borderline requests with high generation quality and controllability.
• Partner with cross-functional teams to distill serving-time classifiers into training rewards and expand the safety and quality trade-off frontier.
• Manage a team of 10 or more researchers and engineers, modeling scientific excellence and building a collaborative culture.

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.