Machine Learning Engineer - Orchestration
San Jose, California, United States
USD 212K-450K Senior-level Full Time
Tasks
- Build distributed training runtime for recommendation models
- Build online inference orchestration architecture
- Design distributed training APIs and runtime
- Develop distributed scheduling frameworks
- Implement AutoScaling and parallelization
- Integrate model research into MLOps process
- Manage service preemption and eviction
- Optimize diagnostics and usability for distributed training
- Optimize distributed orchestration and scheduling
- Optimize resource requests using load modeling
- Optimize scheduling across data centers regions and clouds
- Support mixed deployment across resources and clusters
Perks/Benefits
- N/A
Skills/Tech-stack
Autoscaling | Distributed Systems | Embedding | Eviction | GPU | Kubernetes | Load Modeling | MLOps | Machine Learning | Model Parallelism | Preemption | Python | Recommendation Systems | Scheduling
Education
N/A
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