Job Description
- Required Qualifications
- Experience: 3+ years of experience in MLOps, DevOps, or Software Engineering with a focus on machine learning systems.
- Programming: Expert proficiency in Python and solid experience with writing clean, production-level code.
- Cloud & Containerization: Strong experience with a major cloud provider (AWS, GCP, or Azure) and expert knowledge of containerization technologies (Docker, Kubernetes).
- MLOps Tools: Hands-on experience with MLOps frameworks and platforms (e.g., MLflow, Kubeflow, Sagemaker, TFX, or similar).
- Technical Foundation: Deep understanding of the machine learning lifecycle, from data prep and model training to deployment and monitoring.
- Preferred Qualifications
- Experience working in the HealthTech or FinTech industries, particularly with highly regulated data.
- Experience designing and managing data pipelines (ETL/ELT) for ML features.
- Knowledge of data governance, security principles, and compliance requirements in healthcare (e.g., HIPAA).
- Experience optimizing models for latency and throughput (e.g., ONNX, model quantization).
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
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