Senior Research Engineer

Google•New York, NY

8h•$174,000 - $253,000

About The Position

At Google DeepMind, the Senior Research Engineer will work with scientists, engineers, and machine learning experts to advance artificial intelligence. The team applies its technologies to public benefit and scientific discovery, collaborates on critical challenges, and prioritizes safety and ethics. The role focuses on translating research ideas into practical applications by developing and deploying optimized machine learning systems, implementing scalable software libraries, and advancing deep neural models and reinforcement learning algorithms. It also involves leading long-term research projects and contributing to engineering practices and communication across research and engineering teams.

Requirements

PhD in Computer Science, Engineering, Computer Information Systems, Mathematics, Physics, or a related field and 2 years of experience in the job offered or a Research Engineer-related occupation; alternatively, a master's degree in one of these fields and 5 years of such experience.
2 years of experience developing with TensorFlow, JAX, or PyTorch machine learning frameworks.
2 years of experience leading a research agenda.
2 years of experience applying research from proof of concept to implementation.
2 years of experience applying machine learning theory.
2 years of experience using Python or C++.

Responsibilities

Apply research ideas to high-impact problems through prototyping, dataset curation, and deployment of optimized machine learning systems.
Architect and implement scalable software libraries and high-quality code in Python or C++ to translate complex research into practical applications.
Drive high-stakes, long-term research projects from ideation to completion by scoping project needs, managing resources, and solving ambiguous problems.
Train, evaluate, and iterate on deep neural models and reinforcement learning algorithms to improve agent performance and achieve research objectives.
Influence engineering best practices by championing code reviews, mentoring team members, and facilitating clear communication between research and engineering.
Communicate research developments, experimental results, and project status to internal teams and the broader external community.