Staff Research Scientist, Google Cloud Ai Research
Google
Sunnyvale, CA, United States
Base: $207,000-$300,000; bonus/equity: included bu...
Not specified (potential for hybrid or on-site based on company norms).
Machine learning and deep learning expertise
Natural language processing skills
Data mining and analysis capabilities
Google is seeking a Staff Research Scientist for its Cloud AI Research team in Sunnyvale, CA. The role involves developing innovative AI solutions, conducting large-scale tests, and contributing to the research community while collaborating with product teams to implement findings
Job Summary
The role involves setting up large-scale tests and deploying promising ideas quickly while managing deadlines and deliverables.
Researchers are expected to actively contribute to the wider community by sharing findings through publications and collaborations with external institutes.
The position focuses on pushing the state-of-the-art in AI to address real-world challenges across industries like healthcare, finance, and retail.
Matching Summary
Match Score: 85
Google is seeking a Staff Research Scientist for its Cloud AI Research team in Sunnyvale, CA. The role involves developing innovative AI solutions, conducting large-scale tests, and contributing to the research community while collaborating with product teams to implement findings.
Salary
Base: $207,000-$300,000; Bonus/Equity: Included but not specified; Benefits: Not specified
Skills & Requirements
Must-have
Machine Learning and Deep Learning expertise
Natural Language Processing skills
Data Mining and analysis capabilities
Research paper authorship experience
Large-scale experiment design
Nice-to-have
Collaboration with partner universities
Experience reviewing academic papers
Serving on program committees
Hardware and software performance analysis
Compiler improvement for mobile platforms
Key Requirements
PhD or equivalent advanced degree in Computer Science or related field
Proven track record of publishing research papers
Ability to define data structures and evaluation metrics for solutions