Staff Research Engineer, Applied AI, DeepMind

Experteer Overview In this role you will translate AI research into real-world products at Google DeepMind. You will lead cross-functional work to define objectives and technical designs, curate specialized datasets, and evaluate models across domains. You’ll build novel AI-powered solutions from idea to production, using DeepMind foundation models, and share learnings with core research teams. You’ll shape best practices for responsible, high-impact generative AI deployment and demonstrate frontier model capabilities. Compensation / Benefits * Collaborate with external partners and internal teams to clarify product objectives and technical designs in ambiguous problems * Curate specialized datasets, design evaluation pipelines, and fine-tune models for real-world performance * Lead end-to-end development of novel AI solutions from concept to production leveraging internal platforms and foundation models * Synthesize partner learnings and deployment signals to inform frontier model research * Act as a technical leader, setting best practices for generative AI deployment and end-to-end impact * Translate research ideas into scalable AI-powered software and features for large-scale use Tasks * Bachelor’s degree in Electrical Engineering, Computer Engineering, Computer Science, or related field * 8 years of software development experience including system design, data structures, and algorithms * 5 years of experience building, training, and deploying ML models into production environments Key requirements * bonus target (20%) * equity * benefits

aav_ * Act as a technical leader, setting best practices for generative AI deployment and end-to-end impact * Translate research ideas into scalable AI-powered software and features for large-scale use Tasks * Bachelor’s degree in Electrical Engineering, Computer Engineering, Computer Science, or related field * 8 years of software development experience including system design, data structures, and algorithms * 5 years of experience building, training, and deploying ML models into production environments Key requirements * bonus target (20%) * equity * benefits