Machine Learning Engineer (MLE) - MLOps - Healthcare or Life Sciences sector.

Ahura Workforce Solutions is seeking a production-focused Machine Learning Engineer (MLE) to prioritize the engineering, deployment, and scalability of machine learning systems. The role involves moving models from research to production and ensuring compliance with industry standards.

Responsibilities:

• MLOps on AWS: Lead the end-to-end MLOps lifecycle within the AWS ecosystem, with a focus on CI/CD for machine learning and automated model monitoring
• Infrastructure & Data Modeling: Design and implement scalable infrastructure architecture, including complex data models specifically structured for ML workloads
• ML Pipelines: Build and maintain automated pipelines to handle data ingestion, preprocessing, training, and deployment at scale
• Feature Engineering: Develop and optimize sophisticated feature engineering workflows to enhance model accuracy and operational efficiency
• Regulatory & Data Engineering: Bridge the gap between data engineering and model deployment while adhering to strict regulatory requirements inherent to the life sciences industry

Requirements:

• Proven track record as an MLE with experience productionizing models (rather than just DS/Analytics)
• Expert knowledge of AWS (SageMaker, Lambda, Glue) for ML applications
• Strong background in data engineering, ETL design, and data modeling
• Experience in the Healthcare or Life Sciences sector
• Understanding of regulatory experience and working within regulated data environments
• Bachelor's degree in Business Administration, Information Technology, or a related field