Head of Research, Professional Intelligence, DeepMind

• Act like an owner; be fearless in diving deep, asking questions, proposing solutions, establishing consensus and then making things happen.
• Lead, mentor, and grow a team of research scientists and machine learning engineers.
• Provide direction and focus in areas of high ambiguity while prioritizing team workloads and managing projects to enable rapid iteration on research initiatives.
• Oversee the development of benchmark datasets and rigorous evaluation suites measuring factual accuracy, citation fidelity, and multi-step reasoning.
• Partner with engineering, product management, and legal domain experts to deploy research advances to early enterprise partners.

Minimum qualifications:

• PhD in Computer Science, Mathematics, Applied Statistics, Machine Learning, or a related quantitative field, or equivalent practical experience.
• 10 years of experience in applied NLP research and productionization, including experience with advanced prompting, and LLM fine-tuning or reinforcement learning (RL).
• 4 years of experience leading technical or research teams and mentoring engineers.

Preferred qualifications:

• Startup experience iterating fast and exploring multiple strategies to optimize performance.
• Exposure to production systems that rely on ML models, or experience with model deployment.
• Significant success with building AI software and systems for specific industries, either as research publications at top PL or ML venues, or as open source artifacts.
• Track record of delivering high quality solutions to large, complex software problems.
• Work Independently, committed to safe, transformative AI, and excellent written and verbal communication and strong stakeholder management across all levels.
• Demonstrated ability to deliver clean, maintainable, production-grade code in Python, adhering to sound engineering principles.

• PhD in Computer Science, Mathematics, Applied Statistics, Machine Learning, or a related quantitative field, or equivalent practical experience.
• 10 years of experience in applied NLP research and productionization, including experience with advanced prompting, and LLM fine-tuning or reinforcement learning (RL).
• 4 years of experience leading technical or research teams and mentoring engineers.