In this role, you will build and maintain the machine learning infrastructure that supports production AI within Solventum’s Healthcare Information Systems (HIS). You will connect data science and software engineering through automated workflows, cloud operations, secure service delivery, and practical monitoring.
Role Overview
As an ML Engineer, you will ensure reliable model performance in real-world healthcare workflows. The position emphasizes production-grade pipelines, scalable deployment patterns for clinical use, and disciplined handling of regulated healthcare data. Work will include CI/CD for machine learning, ETL and dataset preparation using healthcare standards (FHIR, HL7), and integration with core backend systems.
Responsibilities
- Build and maintain CI/CD pipelines for machine learning, including automated testing, model deployment, and version control (for example, using MLflow and Git).
- Deploy machine learning models as scalable APIs and microservices, meeting performance and latency needs for clinical use.
- Implement monitoring to track model performance, data drift, and overall system health in production.
- Develop and optimize ETL processes that transform healthcare data (FHIR, HL7) into clean, usable datasets for training and inference.
- Help build and maintain feature stores and data layers to ensure consistency between training and production environments.
- Collaborate with backend teams to integrate ML outputs into Solventum’s core healthcare applications.
- Write clean, maintainable, and well-documented Python code.
- Participate in code reviews to support reliability across systems.
- Use Docker and Kubernetes to package and orchestrate machine learning workloads across environments.
- Follow established HIPAA and HITRUST security protocols for data handling and deployments.
Required Qualifications
- Bachelor’s or Master’s degree in Computer Science, Software Engineering, or Data Engineering.
- 4 years of professional experience in software engineering or data engineering, including at least 2 years focused on machine learning production environments.
- 2 years of experience with Python and SQL.
- Knowledge of a compiled language (such as Go or Java).
- 2 years of hands-on experience with at least one major cloud provider (AWS, Azure, or GCP) and Docker containerization.
- 2 years of experience with ML libraries (PyTorch or Scikit-learn) and MLOps tools (Airflow, Prefect, BentoML, or Kubeflow).
- 2 years of experience with data processing frameworks (Pandas, Spark, or dbt).
Technologies and Tools
- MLflow, Git, Python, SQL
- Go, Java
- AWS, Azure, GCP
- Docker, Kubernetes
- PyTorch, Scikit-learn
- Airflow, Prefect, BentoML, Kubeflow
- Pandas, Spark, dbt
- FHIR, HL7, APIs, microservices
- HIPAA, HITRUST
Helpful Additional Qualifications
- Familiarity with deploying Large Language Models (LLMs) or using frameworks such as LangChain.
- Experience working in a regulated environment (Healthcare, Finance, or similar).
- Understanding of API design and microservices architecture.
Location and Work Model
Location: Pittsburgh, PA (remote)
Travel: May include up to 10% domestic
Compensation
The expected compensation range for this position is $106,000 - $145,750 per year, including base pay plus variable incentive pay, if eligible.
Onboarding and Travel for New Hires
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. This applies to new hires with a start date of October 1, 2025 or later.
Application Integrity Notice
Solventum is committed to maintaining high standards of integrity and professionalism in its recruitment process. Applicants must remain alert to fraudulent job postings and recruitment schemes that falsely claim to represent Solventum and seek to exploit job seekers.
Please note that all email communications from Solventum regarding job opportunities with the company will be from an email with an appropriate Solventum domain. Be wary of unsolicited emails or messages regarding Solventum job opportunities from emails with other email domains.
