AI Research Engineer (Agentic Post-training)
Tasks
- Build benchmarking systems
- Build multi agent coordination
- Collaborate with research and product teams
- Conduct end to end post training research
- Create evaluation frameworks
- Curation of training data
- Design post-training pipelines
- Develop diagnostic systems
- Develop training infrastructure
- Identify system bottlenecks
- Implement tool function calling
- Improve factuality
- Improve instruction following
- Improve multi step reasoning
- Integrate production feedback into training
- Optimize efficiency reliability and performance
Perks/Benefits
- Collaborative research environment
- Continuous learning
- Professional growth opportunities
- Remote-first environment
Skills/Tech-stack
Agent systems | Agentic AI | Benchmarking | Data Curation | Deep learning | Distributed Training | Fine Tuning | Function Calling | Instruction Tuning | Language Models | Language Processing | Large Language Models | Model Evaluation | Multi-Agent | Multi-Agent Systems | Multi-GPU | Multi-node | Multimodal Learning | Natural Language | Natural Language Processing | Post-training | Reinforcement Learning | Tool use | Training pipelines
Education
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