Research Engineer developing conditional generative adversarial networks for synthetic microstructures in PMC and CMC. Collaborating with AFRL and advancing materials performance through data - driven insights.
About the role
- Research Engineer developing scalable tools for reward models at Anthropic. Collaborating with researchers to enhance AI system training effectiveness.
Responsibilities
- Design and build infrastructure for researchers to iterate on reward signals
- Develop systems for automated quality assessment of rewards
- Create tooling for comparing reward methodologies
- Build pipelines to reduce toil in reward development
- Implement monitoring systems to track reward signal quality
- Collaborate with researchers to translate science requirements into platform capabilities
- Optimize existing systems for performance and reliability
Requirements
- Have prior research experience
- Strong Python skills
- Experience with ML workflows and data pipelines
- Building related infrastructure/tooling/platforms
- Comfortable working across the stack
- Results-oriented with a bias towards flexibility and impact
- Care about the societal impacts of your work
Benefits
- Competitive compensation and benefits
- Equity options
- Generous vacation
- Parental leave
- Flexible working hours
- Lovely office space for collaboration
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