Machine Learning Engineer
Tasks
- Build MLOps infrastructure
- Create automated continuous model retraining pipelines
- Deploy low latency machine learning inference services
- Design model tracking and registry
- Develop multi model AI architectures
- Evaluate and optimize tool TCO and technical overhead
- Implement model serving and monitoring
- Manage data and feature pipelines
- Set engineering standards for ML organization
- Translate machine learning prototypes into production code
Perks/Benefits
Skills/Tech-stack
AWS EC2 | AWS EKS | Airflow | Amazon SageMaker | CI/CD | DBT | Datadog | Docker | DynamoDB | FastAPI | Feast | Feature Store | Inference Server | Kubeflow | Kubernetes | MLOps | MLflow | Machine Learning | Metaflow | ONNX | Prometheus | PyTorch | Python | Ray Serve | Redis | S3 | Snowflake | TensorFlow | TensorRT | Terraform | Torchserve | Triton Inference | Triton Inference Server | Vector Databases | Weights and Biases
Education
N/A
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