Staff Research Engineer, Applied AI, DeepMind

Job description

Partner closely with multiple external parties and internal cross-functional teams to navigate ambiguity, deeply understand real-world issues, and define clear product objectives and technical designs. Drive the curation of specialized datasets, design evaluations across industry verticals, and execute model fine-tuning to achieve optimal real-world performance. Lead the engineering and development of novel solutions from 0 to 1, utilizing internal platforms and tools to build sophisticated agents and workflows powered by DeepMind foundation models. Synthesize and upstream learnings from third-party partners to our core research teams, by sharing real-world evaluations, edge cases, and deployment signals, which can inform the development of future frontier models. Act as a technical leader in the applied AI space, setting best practices for generative AI deployment and demonstrating the peak capabilities of frontier models in solving high-impact problems end-to-end. Minimum Qualifications: Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience. 8 years of software development experience, including system design, data structures, and algorithms. 5 years of experience building, training, and deploying machine learning models into production environments. Preferred Qualifications: Experience working with Generative AI/LLMs, specifically in model fine-tuning, custom dataset curation, and designing evaluation pipelines. Proven experience architecting, prototyping, and shipping complex ML systems from the ground up, with a deep understanding of machine learning and deep learning (e.g., Transformers, Diffusion, LLMs). Good communication skills with a proven ability to engage with cross-functional teams, and take ambiguous, open-ended real-world problems and translate them into clear technical designs and product scope.