We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.
Responsibilities
- Build and optimize multi-agent hierarchical pipelines and cross-application reasoning agents for productivity agents.
- Develop, scale, and maintain automated evaluation raters to assess model capabilities under complex, real-world conditions.
- Maintain secure execution environments (Python Workspace API harnesses, Bash/gws CLI) to evaluate agent trajectories hermetically, and allow for large-scale distillation and training in the environments.
Minimum qualifications:
- Experience building systems powered by LLMs or other ML models.
- Experience in software development in training, developing or applying machine learning models.
Preferred qualifications:
- Strong AI development knowledge, training GenAI models.
- Strong software engineering fundamentals, with a track record of shipping production-quality code.
- Strong collaboration and communication skills across research, engineering and product teams.
- Interest in AI agents and how they can make people more productive.
- Comfortable working in an ambiguous, changing research and product environment.