ML Engineer

Job Description

ML Engineer – Solventum (formerly 3M Health Care).

The role focuses on building and maintaining pipelines that power AI in our Healthcare Information Systems (HIS).

You will bridge the gap between data science and software engineering by implementing automated workflows, managing cloud infrastructure, and ensuring our AI services are secure and scalable.

The Impact You’ll Make in this Role

As an ML Engineer, you will be responsible for building and maintaining the pipelines that power AI in our Healthcare Information Systems (HIS).

We are looking for a practical, detail‑oriented engineer who is passionate about MLOps, data reliability, and production stability.

In this role, you won’t just be building models; you will be ensuring those models work reliably in the real world.

You will help bridge the gap between data science and software engineering by implementing automated workflows, managing cloud infrastructure, and ensuring our AI services are secure and scalable.

Key Responsibilities

• MLOps & Deployment
• Pipeline

Development: Build and maintain CI/CD pipelines for machine learning, focusing on automated testing, model deployment, and version control (using tools like MLflow or Git).

• Model Serving: Deploy ML models as scalable APIs and microservices, ensuring they meet performance and latency requirements for clinical use.
• Monitoring: Implement basic monitoring tools to track model performance, data drift, and system health in production.
• Data Engineering & Integration
• Data Pipelines: Develop and optimize ETL processes to transform healthcare data (FHIR, HL7) into clean, usable datasets for model training and inference.
• Feature Management: Build and maintain feature stores and data layers that ensure consistency between training and production environments.
• System Integration: Work closely with backend teams to integrate ML outputs into our core healthcare applications.
• Engineering Best Practices
• Code Quality: Write clean, maintainable, and well‑documented Python code. Participate in code reviews to ensure system reliability.
• Containerization: Use Docker and Kubernetes to package and orchestrate ML workloads across different environments.
• Security & Compliance: Follow established protocols to ensure all data handling and deployments meet HIPAA and HITRUST security standards.
• Your Skills and Expertise
• Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Engineering, or a related field.
• Experience: 3–5 years of professional experience in software engineering or data engineering, with at least 2 years focused on machine learning production environments.
• Programming: Strong proficiency in Python and familiarity with SQL. Knowledge of a compiled language (like Go or Java) is a plus.
• Cloud & Infrastructure: Hands‑on experience with at least one major cloud provider (AWS, Azure, or GCP) and containerization (Docker).
• ML Tools: Familiarity with ML libraries (Py Torch or Scikit‑learn) and MLOps tools (like Airflow, Prefect, Bento ML, or Kubeflow).
• Data Tools: Experience with data processing frameworks (like Pandas, Spark, or dbt).
• Additional qualifications that could help you succeed even further in this role include:
• Familiarity with deploying Large Language Models (LLMs) or using frameworks like Lang Chain.
• Experience working in a regulated environment (Healthcare, Finance, etc.).
• Understanding of API design and microservices architecture.
• Work location
• Remote
• Travel

May include up to 10% domestic.

Legal and EEO

Must be legally authorized to work in country of employment without sponsorship for employment visa status (e. g., H1B status).

Solventum is an equal opportunity employer.

Solventum will not discriminate against any applicant for employment on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or veteran status.

Onboarding Requirement

New employees hired for this position will be required to travel to a designated company location for on‑site onboarding during their initial days of employment.

Travel arrangements and related expenses will be coordinated and paid for by the company in accordance with its travel policy.

Applies to new hires with a start date of October 1st 2025 or later.

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