Job Description

System Soft Technologies provided pay range

This range is provided by System Soft Technologies. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$75.00/hr - $80.00/hr

Summary :

We are seeking a Machine Learning Operations Engineer with strong experience in the healthcare industry and expertise in deploying and maintaining production-grade machine learning models. The ideal candidate will have a deep understanding of healthcare standards, regulations, and electronic health record (EHR) systems. This role requires technical proficiency in machine learning pipelines, cloud platforms, and compliance standards, as well as a proven ability to collaborate with cross-functional teams to drive innovation in healthcare AI solutions.

Responsibilities:

• ML Model Deployment & Optimization: Deploy, maintain, and scale production-grade machine learning models to ensure real-time inference, reliability, and scalability.
• Pipeline Development: Create and optimize end-to-end AI pipelines, including data ingestion, preprocessing, search, and retrieval processes.
• CI/CD Integration: Build and maintain CI/CD pipelines for machine learning models, automating testing, and deployment processes.
• Monitoring & Logging: Implement monitoring and logging solutions to track model performance, system health, and detect anomalies.
• Collaboration & Leadership: Lead engineering efforts for ML/GenAI model development, large language model (LLM) advancements, and deployment frameworks in alignment with business strategies. Collaborate with data scientists, data engineers, and DevOps teams to achieve project goals.
• Compliance & Security: Ensure all systems meet healthcare-related security and compliance standards, including data protection and privacy regulations.
• Documentation: Maintain clear and comprehensive documentation of ML Ops processes, workflows, and configurations.

Qualifications:

• Bachelor’s degree in Computer Science, Artificial Intelligence, Informatics, or a closely related field. Master’s degree is a plus.
• Minimum of 3 years of relevant experience as a Machine Learning Engineer.
• Proven expertise in deploying and maintaining machine learning models in production environments.
• Strong knowledge of healthcare industry standards, regulations, and systems, including experience integrating ML models with Electronic Health Records (EHR) systems.
• Proficiency in cloud platforms such as AWS, GCP, or Azure for building scalable ML infrastructures.
• Skilled in containerization technologies such as Docker and Kubernetes.
• Strong understanding of security and compliance standards for machine learning systems.
• Experience with version control systems to track changes in ML models and associated code.
• Certifications in machine learning or related fields- a big plus.

Seniority level

Mid-Senior level

Employment type

Contract

Job function

Information Technology and Health Care Provider

Industries

IT Services and IT Consulting

Job Tags

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