About Google
Learn more about Google. Explore our innovative AI products and services, and how we. Backed by Kleiner Perkins.
About the role
As an organization, Google maintains a portfolio of research projects driven by fundamental research, new product innovation, product contribution and infrastructure goals, while providing individuals and teams the freedom to emphasize specific types of work. As a Research Scientist, you'll setup large-scale tests and deploy promising ideas quickly and broadly, managing deadlines and deliverables while applying the latest theories to develop new and improved products, processes, or technologies. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- PhD degree in Computer Science, Machine Learning, or a related technical field, or equivalent practical experience
- Experience in Python and deep learning frameworks (e.g., JAX, Flax, or Gemma)
- Experience in developing multimodal AI models and systems
- Experience conducting research and development, including experimental design, implementation, and analysis
- Publication record in machine learning conferences (e.g., NeurIPS, CVPR, ICML, ICLR, ICCV, ECCV)
More about this role
- Generate new ideas, keep up with the state-of-the-art in the field, and discuss research directions with other researchers.
- Design, rapidly implement, and evaluate ideas, methods, interfaces, and tools to explore new sociotechnical AI systems.
- Report and present research findings and developments clearly and efficiently both internally and externally, verbally and in writing.
- Suggest and engage in inter and intra-team collaborations to meet ambitious research goals, while also driving significant individual contributions.
- Take ownership of substantial technical projects, from ideation and design to implementation and evaluation, often involving cross-functional collaboration.
- PhD degree in Computer Science, Machine Learning, or a related technical field, or equivalent practical experience.
- Experience in Python and deep learning frameworks (e.g., JAX, Flax, or Gemma).
- Experience in developing multimodal AI models and systems.
- Experience conducting research and development, including experimental design, implementation, and analysis.
- Publication record in machine learning conferences (e.g., NeurIPS, CVPR, ICML, ICLR, ICCV, ECCV).
- Experience fine-tuning and...
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