AI/ML Research Engineer, LLM Post-Training & Evaluation
Tasks
- Build infrastructure for experimentation and metrics
- Collaborate with data and research scientists
- Contribute to internal R&D and platform development
- Design and improve LLM training pipelines
- Diagnose model and pipeline failures
- Implement evaluation systems and benchmarks
- Integrate human-in-the-loop and AI evaluation signals
- Lead technical ML projects
- Mentor junior engineers
- Work with customer stakeholders to understand goals
Perks/Benefits
Skills/Tech-stack
Data Pipelines | Debugging | Distributed Training | Experiment tracking | Fine Tuning | Hugging Face | JAX | Large Scale ML | Large-scale ML systems | ML Systems | ML Systems Engineering | ML evaluation | Model Evaluation | Model Fine-tuning | Performance optimization | PyTorch | Python | Reproducibility | Systems engineering | TensorFlow
Education
AI | Applied Mathematics | Bachelor | Machine Learning | Master | PhD in Computer Science
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