AI Research Engineer (Agentic Post-training)
Tasks
- Advance post training methods for agentic AI systems
- Build and optimize large scale post training pipelines
- Collaborate with research engineering and product teams for scalable integration
- Create benchmarking and diagnostic systems for reliability
- Design data curation workflows for AI training
- Develop training infrastructure and evaluation frameworks
- Identify system bottlenecks and propose efficiency improvements
- Improve factuality instruction following multi step reasoning and tool function calling
- Integrate production feedback signals into training loops
Perks/Benefits
- Collaborative research environment
- Continuous learning
- Globally distributed team
- Professional growth
- Remote-first
Skills/Tech-stack
Agent coordination | Data Curation | Deep learning | Distributed Training | Fine Tuning | Function Calling | Instruction Tuning | Language Models | Large Language Models | Model Benchmarking | Model Evaluation | Multi-Agent | Multi-Agent Coordination | Multi-GPU | Multi-node | Multimodal Learning | Post-training | PyTorch | Python | Reinforcement Learning | Tool use | Training Pipeline
Education
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