ML Engineer, Post-Training and Evaluation
Tasks
- Build evaluation harnesses
- Build reproducible data pipelines
- Clean and format training data
- Curate baselines and measure improvements
- Debug training and inference issues
- Design evaluation suites and test sets
- Fine-tune language models
- Interpret training loss curves
- Prepare datasets and training runs
- Support model deployment to production
Perks/Benefits
- Dental insurance
- Disability insurance
- Health insurance
- Life insurance
- Paid time off
- Parental leave
- Relocation support
- Vision insurance
Skills/Tech-stack
Data Pipelines | Data Quality | Data quality analysis | Dataset Preparation | Evaluation methodology | Experiment tracking | Fine Tuning | GPU Computing | Human Feedback | Inference Optimization | Language Models | Learning from Human Feedback | Machine Learning | Preference optimization | Python | Quality analysis | Reinforcement Fine Tuning | Reinforcement Learning | Reinforcement Learning from Human Feedback | Supervised Fine Tuning | Version control
Education
N/A
Regions
Countries
States
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