Agent Post-Training, Computer Use Research
Tasks
- Build evals and environments for model failures
- Debug hard failures and create experiments and fixes
- Decide integrations for major model runs
- Design and run experiments for computer use agents
- Implement early training and alignment interventions
- Improve large scale training reliability and observability
- Own post training stack improvements
- Translate product signals into model improvements
Perks/Benefits
- N/A
Skills/Tech-stack
Data pipeline | Evaluation | Experimentation | Grader Development | Machine Learning | Model Training | Post-training | RLAIF | RLHF | Reinforcement Learning | Reward Modeling | Synthetic data | Systems engineering
Education
N/A
Regions
Countries
States
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