Staff Research Scientist/Engineer, Agentic Post Training, DeepMind
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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; New York, NY, USA; San Francisco, CA, USA.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience testing, and launching software products.
- 3 years of experience with software design and architecture.
- 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.
- 3 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, candidates with primarily ML infrastructure (ML infra) backgrounds will likely find this is not the right profile for their skill set.
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: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
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.
Seen 2 days ago · Google DeepMind postings close after a median of 9 days.
Original posting on Google DeepMind's site ↗
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