Staff Research Scientist: Agent Post-Training, Equity

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

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

Life insurance

Disability insurance

401(k) with company match

Paid time off

Sick time

Maternity leave

Baby bonding leave

Holidays

Job summary

Google DeepMind is seeking a Staff Research Scientist/Engineer to advance Agent Post-training and Personalization for consumer agents. You will lead research on reinforcement learning, data creation, and persistent context architectures to keep user state reliable over time while scaling evaluation frameworks for long-horizon reasoning.

The role emphasizes developing datasets, evaluation tools, and scalable research infrastructure within a world-class AI lab; equity and competitive compensation

Qualifications

• Bachelor’s degree or equivalent practical experience required.
• 8 years of software development experience and 5 years of testing and launching software products.
• Experience with large language models, RL, and deep learning.

Responsibilities

• Specialize in core modeling and post-training for agent post-training.
• Design ablation studies and validate research hypotheses.
• Communicate findings through visualizations and reports.
• Develop research infrastructure for data analysis and model evaluations.
• Collaborate with researchers and engineers on ongoing projects.

Skills

Large language models

Reinforcement learning

Deep learning

Software development

Python

Research communication

Education

Bachelor’s degree or equivalent practical experience

Master’s degree or PhD in Engineering, Computer Science, or related field

Tools

TensorFlow

PyTorch

Job description

Google DeepMind is seeking a Staff Research Scientist/Engineer to advance Agent Post-training and Personalization for consumer agents. You will lead research on reinforcement learning, data creation, and persistent context architectures to keep user state reliable over time while scaling evaluation frameworks for long-horizon reasoning.

The role emphasizes developing datasets, evaluation tools, and scalable research infrastructure within a world-class AI lab; equity and competitive compensation