AI Research Engineer (Agentic Post-training)
Tasks
- Build multi agent coordination
- Conduct research and engineering for post training agentic AI
- Create benchmarking systems
- Create diagnostic systems
- Curate training data
- Design training pipelines for large scale post training
- Develop evaluation frameworks
- Enable multi step reasoning
- Identify system bottlenecks
- Implement tool function calling
- Improve efficiency reliability and performance of tool augmented models
- Improve instruction following
- Improve model factuality
- Integrate production feedback into training loops
Perks/Benefits
- Continuous learning
- Global distributed team
- High impact ownership
- Professional growth
- Remote-first work environment
Skills/Tech-stack
Agent coordination | Benchmarking | Data pipeline | Distributed Training | Fine Tuning | Function Calling | Instruction Tuning | Language Models | Large Language Models | Learning Research | Machine Learning | Machine learning research | Model Evaluation | Model diagnostics | Multi-Agent | Multi-Agent Coordination | Multi-GPU | Multi-node | Multimodal Learning | Open Source | Post-training | Reinforcement Learning | Tool use
Education
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