Research Scientist
This job at a glance
- Who can apply
- New grads, no experience needed · Master's degree
- Must know
- Data structures & algorithmsLLMsMachine learning
- Work
- On-site in Mountain View
- Pay
- Not stated by the employer.
- Skill demand
- Machine learning28%Data structures & algorithms12%LLMs9%of 100 similar entry-level jobs posted in the US this week
- Listed
- Nov 6, 2026 · still open
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About The Job
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.
Key Responsibilities
- Drive an ambitious research agenda in post-training, reinforcement learning, and agentic modeling to improve Gemini's reasoning, tool use, factuality, and multimodal performance across global languages, dialects, and locales.
- Develop scalable algorithms for cross-lingual capability transfer, synthetic data generation, reward modeling, and self-improvement flywheels that close the quality gap for both major global languages and low-resource languages.
- Improve local and cultural grounding, factuality, naturalness, and language consistency across long-horizon multi-turn and multimodal interactions (text, speech, image, and video).
- Design trustworthy evaluation methodologies, evaluations, and human-grounded reward signals to measure and steer complex agentic and culturally nuanced model behaviors.
- Partner closely with core Gemini post-training, agentic, and pretraining/mid-training teams—as well as product partners across Google—to land research breakthroughs directly into flagship Gemini models.
Requirements & Tech Stack
- Experience with research in one or more of the following areas: LLM post-training and alignment, reinforcement learning, multilingual benchmarking, reasoning and agentic systems, or foundation model training.
- Experience training, post-training, or evaluating foundation models.
Qualifications
- Master's degree in Computer Science, Machine Learning, Artificial Intelligence, Mathematics, or a related technical field, or equivalent practical experience.
- Ability to translate open-ended research ideas into landed improvements in frontier models across multi-team collaborations.
- Excellent communication and collaboration skills.
- A genuine passion for human languages and building AI that works for people everywhere.