Machine Learning Engineer - Orchestration
San Jose, California, United States
USD 162K-250K (estimate) Mid-level Full Time
Tasks
- Build distributed training runtime for large scale recommendation models
- Build online model inference orchestration architecture
- Design multi data center region and multi cloud scheduling
- Develop Kubernetes based scheduling frameworks
- Develop distributed training APIs and runtime
- Implement service preemption and eviction
- Improve distributed training diagnosability and usability
- Integrate research and experimentation into MLops workflows
- Optimize autoscaling for model resource requests
- Optimize distributed orchestration and scheduling
- Support mixed deployment across clusters
Perks/Benefits
- N/A
Skills/Tech-stack
Apache Flink | Apache Mesos | Auto Scaling | Celery | Deep learning | Distributed Systems | GPU Training | Go | High Performance | High-Performance Computing | Kubernetes | Linux | MLOps | Machine Learning | MapReduce | Parallelization | Performance Computing | PyTorch | Python | Ray | TFX | TensorFlow | YARN
Education
Regions
Countries
States
Cities
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