Senior Research Engineer

Google•Mountain View, CA

8h•$174,000 - $252,000•Hybrid

About The Position

Artificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority. We are pushing the boundaries across multiple domains. Our global teams offer learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.

Requirements

PhD degree in Computer Science, Engineering, Computer Information Systems, Mathematics, Physics, or a related field and 2 years of experience in the job offered or in a Research Engineer-related occupation.
Alternatively, a Master’s degree in Computer Science, Engineering, Computer Information Systems, Mathematics, Physics, or a related field, and 5 years of experience in the job offered or in a Research Engineer-related occupation.
2 years of experience in Python for Software Development and Machine Learning.
2 years of experience in Machine learning and reinforcement learning algorithm design.
2 years of experience in Root cause analysis for debugging ML systems.
2 years of experience in Software design and systems architecture for performance and reliability.
2 years of experience in ML infrastructure development for model deployment, evaluation, and optimization.

Responsibilities

Apply research ideas to high-impact problems by prototyping, curating datasets, and deploying 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-stake, 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 continually 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 clearly to internal teams and the broader external community.