AI Research Engineer (Agentic Post-training)
Tasks
- Advance post training methods for agentic AI
- Build post training pipelines and data curation
- Collaborate with research, engineering, and product teams
- Conduct end to end research and engineering
- Develop benchmarking and diagnostic systems
- Identify bottlenecks and improve efficiency reliability and performance
- Improve factuality instruction following and reasoning
- Integrate production feedback into training loops
- Optimize training infrastructure and evaluation frameworks
Perks/Benefits
- Continuous learning
- High impact ownership
- Professional growth opportunities
- Remote-first work environment
Skills/Tech-stack
Agent systems | Benchmarking | Data Curation | Data Pipelines | Diagnostics | Distributed Training | Fine Tuning | Function Calling | Instruction Tuning | Language Models | Large Language Models | Model Evaluation | Multi-Agent | Multi-Agent Systems | Multi-GPU | Multi-node | Multimodal Learning | Post-training | Reinforcement Learning | Tool use | Training Data Pipelines | Training data
Education
Roles
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