Staff Research Engineer and Scientist, Gemini Post-Training, DeepMind

About the Job

At Google, research-focused Software Engineers are embedded throughout the company, allowing them to setup large-scale tests and deploy promising ideas quickly and broadly. Ideas may come from internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.

From creating experiments and prototyping implementations to designing new architectures, engineers work on real-world problems including artificial intelligence, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more. But you stay connected to your research roots as an active contributor to the wider research community by partnering with universities and publishing papers.

We are looking for a Staff Research Engineer and Scientist with proven experience building large-scale machine learning systems, with expertise in modeling, data engineering and evaluations, to help us develop the best models as part of the Gemini Post-Training team, with a focus on Model Behavior.

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.

Responsibilities

• Develop techniques and data pipelines to optimize frontier Gemini models on key capabilities important for model behavior, i.e., Personality, Information Architecture, and Agent Behavior.
• Build robust and real-world motivated evaluations.
• Partner with surface teams to prioritize modeling needs and ship gemini powered experiences (e.g., GeminiApp, AI mode, etc.).
• Establish best practices for code health and documentation on the team, to facilitate collaboration and reliable development.
• Mentor and guide engineers, fostering their professional growth and development.

Qualifications

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 3 years of experience developing and launching technical products.
• Experience with the domain area of Generative AI and Large Language Models (LLM).

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
• 5 years of experience of research engineering experience (e.g., model training/deployment, efficiency optimization, data pipeline design, ML infrastructure).
• 5 years of experience building robust automatic or human evaluations for ML models.
• 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.