Lead Engineer, Machine Learning
Tasks
- Architect high performance inference systems
- Build data pipelines for real world and synthetic data
- Build training and fine tuning pipelines
- Deploy monitor and improve production models
- Design evaluation systems
- Develop model monitoring for continuous improvement
- Iterate based on real world performance
- Optimize latency GPU utilization memory cost reliability
- Own end to end machine learning systems
- Partner with research and engineering to improve product
Perks/Benefits
- N/A
Skills/Tech-stack
Data pipeline | Deep learning | Fine Tuning | GPU | JAX | Latency optimization | Machine Learning | Model Deployment | Model Evaluation | Model Fine-tuning | Model Inference | Model Monitoring | Model Training | PyTorch | Python | Synthetic data
Education
N/A
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