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Solventum
Solventum
ConsultingHealthcareLogistics
Solventum develops healthcare technologies and services designed to support safer, more efficient medical and oral care. Its portfolio includes advanced wound care, surgical and sterilization solutions, oral care products, health information and technology services, and purification and filtration systems for biopharmaceutical applications. The company also supports healthcare professionals through education and training resources, combining product development with a focus on patient safety, clinical outcomes, and operational efficiency.
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Machine Learning Engineer - Solventum - Pennsylvania Remote

Build production machine learning infrastructure and AI services for Solventum’s healthcare information systems. The role covers MLOps, healthcare data engineering, cloud deployment, monitoring, and compliance.

USUnited StatesPAPennsylvania
$124,000 – $170,500 / year
RemoteFull-timeMiddleSeniorEnglish RequiredMachine Learning Engineer
AirflowAWSDockerETLJavaKubernetesMicroservicesPandasPythonPyTorchScikit-LearnSparkSQL

Description

  • Create and maintain machine learning delivery pipelines, deploy and monitor production models, transform healthcare data, support feature stores, integrate AI into healthcare applications, and maintain secure, documented systems.
  • Deploy machine learning models as scalable APIs and microservices that satisfy clinical performance and latency needs.
  • Monitor model quality, data drift, and the health of production services.
  • Build and improve ETL workflows that convert FHIR, HL7, and other healthcare data into training and inference datasets.
  • Help maintain feature stores and data layers that keep training and production data aligned.
  • Work with backend engineers to integrate machine learning results into core healthcare products.
  • Produce clear, maintainable, and well-documented Python code.
  • Contribute to peer code reviews.
  • Package and orchestrate machine learning workloads with Docker and Kubernetes.
  • Apply HIPAA and HITRUST requirements to data processing and deployments.
  • Travel domestically up to 10%.
  • Complete required on-site onboarding during the first days of employment.

Requirements

  • Bachelor’s degree or higher in computer science, software engineering, data engineering, or a related discipline.
  • At least six years of professional software engineering or data engineering experience.
  • At least five years of Python experience, along with familiarity with SQL.
  • At least two years working with machine learning systems in production.
  • At least five years using AWS and container technologies such as Docker.
  • At least three years of professional Java experience.
  • At least three years using machine learning libraries such as PyTorch or Scikit-learn and MLOps tools such as Airflow, Prefect, BentoML, or Kubeflow.
  • At least four years using data processing frameworks such as Pandas, Spark, or dbt.
  • Familiarity with deploying large language models or working with frameworks such as LangChain.
  • Experience in a regulated industry, including healthcare or finance.
  • Knowledge of API design and microservices architecture.
  • Work must follow corporate policies, procedures, security standards, and documented resume or application requirements.
  • Education and work history must be supplied through a resume or application fields.

Benefits

  • Medical, dental, and vision coverage.
  • Health savings account options.
  • Health care and dependent care flexible spending accounts.
  • Disability benefits.
  • Life insurance.
  • Voluntary benefit programs.
  • Paid absences.
  • Retirement benefits.
  • Company-paid travel and related expenses for required on-site onboarding.
  • Domestic travel of up to 10% may be required.

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