Remote ML Engineer - Production AI for Healthcare

Solventum; Pittsburgh (Allegheny County); Remote; USD 106,000 - 146,000; Full time

Job summary

Solventum is seeking an ML Engineer to build and operate ML pipelines powering healthcare information systems. You will bridge data science and software engineering, implement automated workflows, manage cloud infrastructure, and ensure secure, scalable AI services for clinical use.

The role emphasizes MLOps, data reliability, and production stability, with remote work available and travel up to 10% domestically. Experience with Python, SQL, cloud platforms, and ML libraries is required.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Engineering.
• 4 years of professional software or data engineering experience, with at least 2 years in ML production environments.

Responsibilities

• MLOps & Deployment: build and manage ML pipelines and deployments.
• Pipeline Development: develop CI/CD pipelines for ML with automated testing and version control.
• Model Serving: deploy ML models as scalable APIs/microservices for clinical use.
• Monitoring: implement monitoring for model performance, data drift and system health.
• Data Engineering & Integration: build ETL pipelines and feature stores for training and inference.
• System Integration: integrate ML outputs into core healthcare apps.
• Engineering Best Practices: write clean Python, participate in code reviews.
• Containerization: use Docker and Kubernetes to package workloads.
• Security & Compliance: ensure HIPAA/HITRUST compliance in data handling and deployments.

Skills

Python

SQL

Go/Java

Cloud: AWS/Azure/GCP

Docker

Kubernetes

PyTorch/Scikit-learn

MLflow/Git

Pandas/Spark/dbt

Education

Bachelor’s or Master’s degree in Computer Science/Engineering/Data Engineering

Tools

MLflow

Git

Docker

Kubernetes

Job description

Solventum is seeking an ML Engineer to build and operate ML pipelines powering healthcare information systems. You will bridge data science and software engineering, implement automated workflows, manage cloud infrastructure, and ensure secure, scalable AI services for clinical use.

The role emphasizes MLOps, data reliability, and production stability, with remote work available and travel up to 10% domestically. Experience with Python, SQL, cloud platforms, and ML libraries is required.