About the Role
We 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, and working across partner teams to deliver solutions, and maximize 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 & business impact. Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority. 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.
Responsibilities
- Drive strategic collaborations: Partner closely with multiple 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 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.
Requirements
- Bachelor’s degree in computer science, electrical engineering, or equivalent practical experience.
- 8+ years of software development experience, including robust system design, data structures, and algorithms.
- 5+ years of hands-on experience building, training, and deploying machine learning models into production environments.
- 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).
- Hands-on experience working with Generative AI / LLMs, specifically in model fine-tuning, custom dataset curation, and designing robust evaluation pipelines.
- Strong project track record in one of the following key areas: Generative AI / LLM / Agents, NLP, Computer Vision, Multi-modal AI, Search, or Recommendation Systems.
- Proficiency and hands-on experience with at least one major machine learning framework (e.g., PyTorch, JAX, or TensorFlow).
- 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.
Qualifications
- Prior experience in research and developing GenAI models, or early-stage startups where you balanced business needs with rapid technical execution.
- Familiarity with modern cloud platforms (e.g., GCP, Vertex AI, AWS, Azure) and scalable deployment pipelines.
- Contributions to AI / ML relevant open-source projects.
Benefits
The US base salary range for this full-time position is between $197,000 - $291,000 + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process.