AI Research Engineer (Agentic Post-training)
Tasks
- Advance post training methods for agentic AI systems
- Build multi agent coordination
- Build training infrastructure
- Collaborate on production ready integration
- Create benchmarking systems
- Create diagnostic systems
- Design post training data curation workflows
- Develop evaluation frameworks
- Develop tool and function calling capabilities
- Identify system bottlenecks
- Improve factuality
- Improve instruction following
- Improve multi step reasoning
- Integrate production feedback signals into training loops
- Optimize efficiency reliability and performance
Perks/Benefits
Skills/Tech-stack
Agent systems | Benchmarking | Data Curation | Data pipeline | Deep learning | Distributed Training | Fine Tuning | Function Calling | Instruction Tuning | Language Models | Large Language Models | Machine Learning | Model Evaluation | Model diagnostics | Multi-Agent | Multi-Agent Systems | Multi-GPU | Multi-node | Multimodal Learning | Post-training | Reinforcement Learning | Tool use
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
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