Remote ML Engineer for Healthcare AI & MLOps

USA Solventum Health Information Systems, Inc.; Pittsburgh (Allegheny County); Remote; USD 124,000 - 171,000; Full time

Benefits offered by this job

Medical

Dental & Vision

Health Savings Accounts

Disability Benefits

Life Insurance

Paid Absences

Job summary

Solventum is seeking an ML Engineer to build and maintain ML pipelines powering AI in Healthcare Information Systems. You will ensure models run reliably in production, implement automated workflows, and manage cloud infrastructure to keep services secure and scalable.

You will bridge data science and software engineering, deploying scalable ML workloads with Docker/Kubernetes while meeting HIPAA and HITRUST standards and collaborating with backend teams.

Qualifications

• Bachelor’s degree or higher in Computer Science, Software Engineering, Data Engineering, or a related field.
• 6+ years of professional software or data engineering experience with 5 years Python.
• 2 years of experience in ML production environments.
• 5 years of AWS and containerization (Docker).
• 3 years of Java experience.
• 3 years of ML libraries (PyTorch or Scikit-learn) and MLOps tools (Airflow, Prefect, BentoML, Kubeflow).
• 4 years with data processing frameworks (Pandas, Spark, dbt).
• Familiarity deploying LLMs with LangChain; regulated environments; API design/microservices.

Responsibilities

• MLOps & Deployment: CI/CD pipelines, model deployment, version control.
• Model Serving: APIs and microservices for clinical use.
• Monitoring: track model performance and data drift.

Skills

Python

AWS

Docker

Java

MLOps

Data Engineering

Pandas

Spark

API design

LangChain

Education

Bachelor’s degree or higher

Tools

MLflow

Airflow

Kubeflow

Prefect

BentoML

LangChain

Job description

Solventum is seeking an ML Engineer to build and maintain ML pipelines powering AI in Healthcare Information Systems. You will ensure models run reliably in production, implement automated workflows, and manage cloud infrastructure to keep services secure and scalable.

You will bridge data science and software engineering, deploying scalable ML workloads with Docker/Kubernetes while meeting HIPAA and HITRUST standards and collaborating with backend teams.