Staff Research Scientist, Machine Learning Efficiency
Description For Staff Research Scientist, Machine Learning Efficiency
Google Research is seeking a Staff Research Scientist to lead their Machine Learning efficiency efforts, focusing on next-generation large language models architecture. This role combines cutting-edge research with practical applications, working closely with hardware engineers to co-design high-performance models and next-generation ML accelerators (TPUs). The position involves setting up large-scale tests, deploying innovative ideas, and managing crucial projects that span various computer science domains. The ideal candidate will contribute to the broader research community through publications and collaborations with partner universities worldwide. At Google Research, you'll be part of a team building intelligent systems for all Google products, maintaining the flexibility to adapt to fast-paced business needs. The role offers the opportunity to work with skilled software developers and research scientists, leading innovative solutions in ML efficiency while having a significant impact on future technology development.
Responsibilities For Staff Research Scientist, Machine Learning Efficiency
- Generate, design ideas, leading a team for finding innovative solutions through theoretical or empirical insights
- Design and implementing Machine Learning (ML) algorithms, running and analyzing experiments, incorporating components that could constitute part of a future Tensor Processing Unit (TPU)
- Collaborate with research teams located across the globe
- Define long-term research agendas, intermediate milestones, and align with research and product partners
- Impact through publication and scientific dissemination
Requirements For Staff Research Scientist, Machine Learning Efficiency
- PhD in Computer Science, a related technical field, or equivalent practical experience
- 4 years of experience with research agendas across multiple teams or projects in Machine Learning (ML) efficiency, optimization, or a related field
- Experience with programming languages (e.g., Python, C or C++)
- Experience implementing, running, analyzing experimental models or transformer architecture
- One or more scientific publication submissions for conferences, journals, or public repositories (e.g., ICML, ICLR, NeurIPS)
Jobs Related To Google Staff Research Scientist, Machine Learning Efficiency
