Software Engineer III, Cloud AI Research, Co-Scientist
Indexed description
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience with software development in Python, or 1 year of experience with an advanced degree.
- 1 year of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
- 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
- 1 year of experience with Research and Artificial Intelligence.
- 2 years of experience with data structures and algorithms.
- Experience with software development in C++.
- Experience with system design, distributed computing, machine learning.
- Experience with Research publications.
Cloud AI Research - Co-Scientist is a research team with the mission to accelerate scientific discovery with AI. In this role, you will develop a system for scientific discovery which entails literature research, data analysis, hypothesis generation and validation. The ultimate goal is to build a system that assists scientists from diverse fields with their hardest problems. You will use Google’s latest AI tools and models and have the opportunity to collaborate with scientists in Google and from universities and partner labs.
The Google Cloud AI Research team addresses AI challenges motivated by Google Cloud’s mission of bringing AI to tech, healthcare, finance, retail and many other industries. We work on a range of unique problems focused on research topics that maximize scientific and real-world impact, aiming to push the state-of-the-art in AI and share findings with the broader research community. We also collaborate with product teams to bring innovations to real-world impact that benefits our customers.
Responsibilities
- Develop projects and components end-to-end on the Cloud software stack.
- Build, and deploy agentic AI systems, robust tool-use mechanisms, and multi-agent workflows.
- Analyze datasets, make data driven decisions, develop quality criteria and scoring rubics for AI systems.
- Collaborate with scientists and researchers across Google DeepMind, Google Research, and prestigious external academic partners to publish original research.
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