Senior Staff AI Scientist — Post-Training & LLM Research

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

Benefits offered by this job

Health benefits

401(k) match

Paid time off 20 days/year

Sick time 40 hours/year

Maternity leave 28–30 weeks

Baby Bonding leave

13 paid holidays

Job summary

Google DeepMind is seeking a Senior Staff Research Scientist/Engineer, Agentic Post Training, to advance deep learning, large language models, and reinforcement learning for post-training experiences. This role emphasizes core modeling, evaluation, and collaboration with fellow researchers and engineers.

The candidate will design experiments, communicate results, and contribute to building scalable research infrastructure within a leading AI lab.

Qualifications

• Bachelor’s degree and 8 years of software development experience.
• 5 years of design and architecture experience; launching software products.
• Experience with large language models, reinforcement learning, and deep learning.

Responsibilities

• Specialize in core modeling and post-training experience (e.g., deep learning, LLMs, RL).
• Drive the research process for large-scale agent post-training from hypothesis to delivery.
• Design and execute ablation studies to validate research hypotheses.
• Communicate findings and progress to the team through visualizations and reports.
• Develop research infrastructure and utilities for data analysis and model evaluations.

Skills

Deep learning

Reinforcement learning

Large language models

Research design

Engineering leadership

Cross-functional collaboration

Education

Bachelor's degree

Master's or PhD

Job description

Google DeepMind is seeking a Senior Staff Research Scientist/Engineer, Agentic Post Training, to advance deep learning, large language models, and reinforcement learning for post-training experiences. This role emphasizes core modeling, evaluation, and collaboration with fellow researchers and engineers.

The candidate will design experiments, communicate results, and contribute to building scalable research infrastructure within a leading AI lab.