Research Engineer, Gemini Personalization Research, DeepMind
About The Position
At Google, research-focused Software Engineers are embedded throughout the company to set up large-scale tests and deploy promising ideas quickly and broadly. Ideas may come from internal projects or collaborations with research programs at partner universities and technical institutes. The work can include creating experiments and prototypes, designing architectures, and tackling real-world problems across artificial intelligence, data mining, natural language processing, hardware and software performance analysis, mobile compilers, and core search. Engineers remain active contributors to the research community through university partnerships and publishing papers. At Google DeepMind, interdisciplinary teams advance AI to address complex global challenges and accelerate product innovation for billions of users. The organization applies its technologies for public benefit and scientific discovery, with safety and ethics as priorities. This role focuses on personalization research: advancing post-training techniques, building evaluation frameworks that measure model quality against user behaviors and feedback, and training agents that orchestrate tools and APIs for personalized experiences. Compensation in the US is $174,000–$252,000, plus a 15% bonus target, equity, and benefits. Individual pay depends on job-related skills, experience, and relevant education or training.
Requirements
- Bachelor’s degree or equivalent practical experience.
- Five years of experience designing, constructing, and deploying evaluation frameworks that capture programmatic or algorithmic performance.
Nice To Haves
- One year of agentic memory research experience.
- Experience training and fine-tuning models in environments with accelerators.
- A track record of deploying production-grade AI agents that manage tool use (function calling) and complex state management.
Responsibilities
- Drive research on post-training techniques, including reinforcement learning, supervised fine-tuning, and preference optimization, for personalization scenarios.
- Develop novel evaluation frameworks to measure model quality against user behaviors and feedback.
- Design and train agents capable of orchestrating tools and APIs to deliver hyper-personalized experiences.
Benefits
- 15% bonus target
- Equity
- Benefits
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
