Research Engineer
Tasks
- Build scalable systems for creating validating and deploying RL environments
- Create automated quality assurance pipelines for environment verification
- Create documentation and tools for internal teams and external users
- Customize environment suites and benchmarks for use cases
- Design evaluation frameworks for environment effectiveness
- Develop data curation methods for quality and diversity
- Engage enterprise customers to understand agent training challenges
- Establish reproducible workflows and maintain engineering standards
- Monitor and optimize system performance at scale
- Partner with frontier AI labs to design custom environments
- Present research findings to technical stakeholders
- Prototype environment generation curriculum design and data curation approaches
- Provide technical guidance on agent training and evaluation best practices
- Scale research prototypes into production systems for large deployments
- Stay current with reinforcement learning research
- Translate academic insights into engineering solutions
Perks/Benefits
Skills/Tech-stack
AWS | Agent training | Automated testing | Cloud Computing | Cloud platform | Curriculum Design | Data Curation | Distributed Computing | Evaluation Frameworks | Google Cloud | Google Cloud Platform | JAX | PyTorch | Python | Quality Assurance | Reinforcement Learning | Synthetic data
Education
Roles
Applied Scientist | Engineer | Research Engineer | Scientist
Regions
Countries
States
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