Lead Engineer, Machine Learning
Tasks
- Architect high performance inference systems
- Build data pipelines for training data
- Build training and fine tuning pipelines
- Deploy, monitor, and improve models in production
- Design evaluation systems
- Establish production ML infrastructure
- Iterate on models and systems based on performance
- Own end-to-end ML systems
- Partner with research and application engineering
Perks/Benefits
- N/A
Skills/Tech-stack
Data pipeline | Deep learning | Fine Tuning | GPU Computing | JAX | Machine Learning | Model Deployment | Model Evaluation | Model Inference | PyTorch | Python | Training Pipeline
Education
N/A
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