Cloud MLOps Engineer supporting Data Science and Engineering teams by automating CI/CD pipelines and managing multi - cloud infrastructure for ML production.
About the role
- Machine Learning Engineer focusing on AI and automation solutions for healthcare and life sciences sectors. Designing scalable solutions within AWS/Azure and collaborating with cross-functional teams.
Responsibilities
- Focus on building AI and automation solutions for clients in healthcare and life sciences sectors.
- Work on back-end development, data transformation, experimentation with AI/ML models, and selection of suitable solutions.
- Design scalable and secure solutions within an AWS/Azure based infrastructure.
- Collaborate with cross-functional teams to ensure alignment with client requirements and compliance standards.
- Optimize workflows for security, efficiency, and compliance with lifesciences/healthcare and privacy regulations (e.g., GxP, HIPAA).
Requirements
- Bachelor's degree in Computer Science, Engineering, or a related field. Master's degree or higher is a plus.
- Proficient in designing and implementing ETL pipelines, data transformation, and integration.
- Ability to explore, test, and implement a wide range of machine learning models for diverse problem domains, particularly in OCR, NLP, or document analysis.
- Hands-on experience with AWS services like EC2, Lambda, S3, RDS, VPC etc OR Azure services like Azure Functions, Azure Data Factory, and Azure AI.
- Familiarity with handling sensitive data and meeting regulatory requirements (e.g., HIPAA).
- Strong communication skills and experience working in cross-functional teams.
- Proven ability to lead projects and deliver results within tight timelines.
Job title
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