Staff Research Engineer, Applied AI, Google DeepMind

Job DescriptionWe are seeking a Staff Research Engineer, Applied AI to lead the development and deployment of novel applications leveraging Google’s generative AI models. This role focuses on rapidly developing new features, working across partner teams to deliver solutions, and maximizing impact for Google and top customers. You will be instrumental in translating cutting-edge AI research into real-world products and demonstrating the capabilities of latest-generation models. We are looking for engineers with a strong track record of building and shipping AI-powered software, ideally with experience in early-stage environments where they have contributed to scaling products from initial concept to production. The ideal candidate will be motivated by the opportunity to drive product and business impact.This role requires a strong machine learning foundation and a passion for building and iterating on software products. We are looking for machine learning engineers who thrive in fast-paced environments and have a proven ability to deliver high-quality code. Experience in prototyping, building, and scaling software is essential. We particularly value experience in early-stage or startup environments, where engineers take ownership and drive product development from the ground up.Job ResponsibilitiesDrive strategic collaborations: Partner closely with external parties and internal cross-functional teams to navigate ambiguity, deeply understand real-world challenges, and define clear product objectives and technical designs.Lead the project from ML prototype to final product: Drive the curation of specialized datasets, design rigorous evaluations across diverse industry verticals, and execute model fine-tuning to achieve optimal real-world performance.Architect intelligent systems: 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 GDM foundation models.Drive upstream innovation through third-party insights: 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.Establish industry-leading practices: 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 QualificationsA bachelor degree in computer science, electrical engineering or equivalent experience.8 years of experience in software development with one or more programming languages (e.g., Python) 5 years of experience designing, prototyping, and launching ML systems from the ground up, spanning everything from model training to full production deployment.3 years of experience in Generative AI/LLMs (fine-tuning, dataset curation, evaluation pipelines) and in one of the areas such as Agents, NLP, Computer Vision, Multi-modal AI, Search, or Recommendation Systems.Preferred qualificationsProficiency and hands-on experience with at least one major machine learning framework (e.g., PyTorch, JAX, or TensorFlow).Experience with generative AI research or applications.Experience working in, or founding early stage startupsFamiliarity with modern cloud platforms (e.g., GCP, Vertex AI, AWS, Azure) and scalable deployment pipelines.Contributions to AI / ML relevant open-source projects.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.