Researcher, Computer Use - Agent Post-Training
Tasks
- Build evals and environments
- Convert model failures into training data
- Debug hard failures in near shipped models
- Decide integrations for major training runs
- Design experiments to improve agentic model behavior
- Implement alignment interventions and training objectives
- Improve large scale training and launch systems
- Own post training stack improvements
- Partner with product teams to translate signals into improvements
Perks/Benefits
- N/A
Skills/Tech-stack
Agent systems | Browser Automation | Computer use | Data Pipelines | Desktop Automation | Diagnostics | Evaluation | Experimentation | Grading | Machine Learning | Model Training | Multi-Agent | Multi-Agent Systems | Observability | Post-training | Production Machine Learning | RLAIF | RLHF | Reinforcement Learning | Reproducibility | Statistics | Synthetic data | Systems engineering | Tool use
Education
N/A
Regions
Countries
States
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