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