AI Research Engineer (Agentic Post-training)
Tasks
- Advance post training methods for agentic AI systems
- Build multi agent coordination approaches
- Build training infrastructure
- Collaborate with research, engineering, and product teams
- Create evaluation frameworks
- Curate training data
- Design training pipelines for post training
- Develop benchmarking systems
- Develop diagnostic systems
- Develop tool function calling methods
- Identify system bottlenecks
- Improve factuality
- Improve instruction following
- Improve multi step reasoning
- Integrate production feedback into training loops
- Propose solutions to improve efficiency reliability performance
Perks/Benefits
Skills/Tech-stack
Agent systems | Agentic Workflows | Benchmarking | Data Curation | Diagnostics | Distributed Training | Evaluation Frameworks | Fine Tuning | Function Calling | GitHub | Hugging Face | Instruction Tuning | LLM Systems | Language Models | Large Language Models | Multi-Agent | Multi-Agent Systems | Multi-GPU | Multi-node | Multimodal Learning | Post-training | Reinforcement Learning | Tool use | Training pipelines
Education
Roles
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