ML Engineer

About The Role

The Machine Learning (ML) Engineer at Solventum will play a crucial role in developing, deploying, and maintaining AI-driven solutions within our Healthcare Information Systems (HIS). This position requires a detail-oriented professional who is passionate about MLOps, ensuring data reliability, system stability, and scalable deployment of machine learning models. The successful candidate will bridge the gap between data science and software engineering by creating automated workflows, managing cloud infrastructure, and ensuring that AI services operate securely and efficiently in production environments.

This role involves building robust CI/CD pipelines, deploying models as scalable APIs, and implementing monitoring tools to track performance and data drift. Additionally, the ML Engineer will collaborate with backend teams to integrate AI outputs into core healthcare applications, contributing to Solventum’s mission of delivering smarter, safer healthcare solutions that improve patient outcomes and support healthcare providers.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Engineering, or a related field
• 3–5 years of professional experience in software engineering or data engineering
• At least 2 years of experience working in machine learning production environments
• Strong proficiency in Python programming
• Familiarity with SQL and data processing frameworks (e.g., Pandas, Spark, dbt)
• Hands-on experience with cloud platforms such as AWS, Azure, or GCP
• Experience with containerization tools like Docker and orchestration with Kubernetes
• Knowledge of ML libraries such as PyTorch or Scikit-learn
• Experience with MLOps tools like Airflow, Prefect, BentoML, or Kubeflow
• Understanding of data standards in healthcare such as FHIR and HL7
• Experience working in regulated environments such as healthcare or finance is advantageous
• Knowledge of API design and microservices architecture
• Excellent problem-solving skills and attention to detail
• Strong communication and collaboration skills

Responsibilities

• Design, develop, and maintain CI/CD pipelines for machine learning models, ensuring automated testing, deployment, and version control
• Deploy ML models as scalable APIs and microservices, meeting performance and latency requirements for clinical applications
• Implement monitoring tools to oversee model performance, data drift, and system health in production environments
• Develop and optimize ETL processes to transform healthcare data (FHIR, HL7) into clean, usable datasets for training and inference
• Assist in building and maintaining feature stores and data layers to ensure consistency across training and production environments
• Collaborate with backend teams to integrate AI outputs into healthcare applications seamlessly
• Write clean, maintainable, and well-documented Python code, participating in code reviews to ensure system reliability
• Utilize Docker and Kubernetes for packaging and orchestrating ML workloads across different environments
• Ensure all data handling and deployment activities comply with HIPAA, HITRUST, and other security standards
• Stay updated with the latest trends in MLOps, healthcare data standards, and AI technologies to continuously improve solutions

Benefits

• Competitive salary and comprehensive benefits package
• Remote work flexibility with potential domestic travel up to 10%
• Opportunities for professional growth and development in a cutting-edge healthcare environment
• Participation in innovative projects that directly impact patient care and healthcare delivery
• Supportive and inclusive company culture emphasizing well-being and work-life balance
• Onboarding program including on-site orientation for new hires
• Health and wellness programs to promote physical and financial well-being
• Access to the latest tools, technologies, and resources for continuous learning