Staff Machine Learning Engineer (Platform)
Tasks
- Build experiment management and monitoring systems
- Define contracts between training evaluation and serving
- Define training pipeline roadmap
- Deploy spatial frontier models to global customers
- Design scalable serving for spiky production load
- Develop model serving architecture
- Diagnose and resolve performance bottlenecks
- Enable distributed training with data residency requirements
- Optimize model training using custom CUDA kernels
- Own ML platform strategy end to end
- Standardize ML workflows from experimentation to production
Perks/Benefits
Skills/Tech-stack
AWS | Azure | CUDA | Data Quality | Data Warehousing | Deep learning | Distributed Training | Docker | Experiment Management | GCP | Kubernetes | ML monitoring | Model Serving | PyTorch | Python | Sparse Tensors | System design | Training pipelines
Education
N/A
Regions
Countries
States
Cities
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