Machine Learning Platform Engineer
Tasks
- Build ML infrastructure platforms
- Build model serving and inference infrastructure
- Deploy models and run inference
- Design model training and evaluation systems
- Develop ML data pipelines for training and evaluation
- Enable rapid experimentation for model development and production release
- Implement evaluation and benchmarking for model quality and regressions
- Improve reliability scalability latency throughput and cost efficiency
- Optimize distributed system performance and identify bottlenecks
- Set up observability monitoring tracing and alerting for ML workloads
Perks/Benefits
- N/A
Skills/Tech-stack
Alerting | Benchmarking | Cloud infrastructure | Data Pipelines | Distributed Systems | Evaluation | GPU Performance | High Throughput | High-Throughput Systems | JAX | Low Latency | Low-Latency Systems | Model Deployment | Model Inference | Monitoring | Observability | PyTorch | Python | Retrieval-Augmented Generation | TensorRT-LLM | Tracing | VLLM | Vector Databases | Workflow Orchestration
Education
N/A
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