Senior Staff Research Scientist/Engineer, Consumer Agents Post Training, DeepMind

DeepMind Technologies Limited; Kirkland (WA); On-site; USD 262,000 - 364,000; 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 leave

Maternity leave

Baby bonding leave

Holidays

Job summary

Google DeepMind in the United States is seeking a Research Engineer/Scientist to advance agent post-training and personalization for consumer applications. You will develop methods to convert foundation models into autonomous, adaptive agents and scale them with reinforcement learning and persistent context architectures.

You will build training data, evaluation frameworks, and ensure safety and ethics while pushing the Gemini model recipe forward across multiple domains.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience with design and architecture; and testing/launching software products.
• Experience with large language model, reinforcement learning, and deep learning.

Responsibilities

• Specialize in core modeling and post-training experience. Drive the research process for large-scale agent post-training from hypothesis formulation to delivery in the Gemini model recipe.
• Design and execute ablation studies to validate research hypotheses and accelerate experimental feedback loops.
• Communicate research findings, progress, and outcomes to the broader team through visualizations and reports.
• Develop research infrastructure and utilities for data analysis and model evaluations using standard engineering practices.
• Collaborate with other research scientists and engineers to maintain a regular feedback and communication loop.

Skills

Large language models

Reinforcement learning

Deep learning

Software development

Architecture design

Team leadership

Education

Bachelor's degree or equivalent practical experience

Master's degree or PhD in Engineering/CS

Tools

TensorFlow

PyTorch

Job description

In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:

• Health, dental, vision, life, disability insurance
• Retirement Benefits: 401(k) with company match
• Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
• Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
• Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
• Baby Bonding Leave: 18 weeks
• Holidays: 13 paid days per year

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.

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

Minimum qualifications

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience with design and architecture; and testing/launching software products.
• Experience with large language model, reinforcement learning, and deep learning.

Preferred qualifications

• Master's degree or PhD in Engineering, Computer Science, or a related technical field.
• 8 years of experience with data structures and algorithms.
• 5 years of experience in a technical leadership role leading project teams and setting technical direction.
• 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.

About the job

This role is dedicated to core modeling and post-training experience (e.g., deep learning, LLMs, and reinforcement learning). Because of this focus, applicants with primarily ML infrastructure (ML infra) backgrounds will likely find this is not the right profile for their skill set.

As a Research Engineer/Research Scientist, you will work on Agent Post-training and Personalization to build Consumer Agents. You will research, develop and scale foundational post-training methods that convert foundation models into autonomous, adaptive agents for consumers. Your focus centers on reinforcement learning, targeted data creation, and persistent context architectures so models retain user-specific state reliably over time and adapt to individual users.

Additionally, you will build training datasets and evaluation frameworks to test long-horizon reasoning, uncover failure modes, and measure agent reliability across complex workflows.

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 .

• Specialize in core modeling and post-training experience. Drive the research process for large-scale agent post-training from hypothesis formulation to delivery in the Gemini model recipe.
• Design and execute ablation studies to validate research hypotheses and accelerate experimental feedback loops.
• Communicate research findings, progress, and outcomes to the broader team through visualizations and reports.
• Develop research infrastructure and utilities for data analysis and model evaluations using standard engineering practices.
• Collaborate with other research scientists and engineers to maintain a regular feedback and communication loop.

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 .