Agent Post-Training, Context Research
Tasks
- Analyze model failures
- Build data pipelines
- Create training data from failures
- Debug model failures
- Design and run experiments
- Develop evals and environments
- Implement RL and post training interventions
- Improve post training stack
- Measure results and ship improvements
- Partner on product driven model improvements
- Scale compute on context
Perks/Benefits
- N/A
Skills/Tech-stack
Data Pipelines | Deep learning | Experimentation | Grading | Language Models | Language Processing | Large Language Models | Machine Learning | Model Evaluation | Natural Language | Natural Language Processing | Observability | RLAIF | RLHF | Reinforcement Learning | Reproducibility | Reward Modeling | Statistics | Synthetic data | Systems engineering
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Regions
Countries
States
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