Machine Learning Engineer

Solventum

. Build and maintain CI/CD pipelines for machine learning, including automated testing, model deployment, and version control .

Posted 10/7/2026full-timeRemote • Pennsylvania • United StatesMid-LevelSenior💰 $106,000 - $145,750 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in building and maintaining CI/CD pipelines for machine learning, deploying scalable APIs, and optimizing ETL processes in healthcare. Proficient in Python, SQL, and MLOps tools, with a strong focus on compliance with HIPAA and HITRUST standards.

Highest-signal resume keywords

CI/CD Pipeline DevelopmentMachine Learning Model DeploymentPython ProgrammingMLOps Tools ExperienceData Processing Frameworks

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

PythonSQLMachine LearningETL ProcessesDockerKubernetesMLOpsPandasPyTorchScikit-learn

Soft Skills

Code Review ParticipationDocumentation Skills

Tools & Technologies

AWSAzureGCPAirflowPrefectBentoMLKubeflowFHIRHL7Spark

Industry Keywords

HIPAA ComplianceHITRUST ComplianceHealthcare DataData Drift MonitoringModel Performance Monitoring

Tech Stack

Tools & technologies

AirflowAWSAzureCloudDockerETLGoogle Cloud PlatformJavaKubernetesMicroservicesPandasPythonPyTorchScikit-LearnSparkSQLGo

About the role

Key responsibilities & impact

Build and maintain CI/CD pipelines for machine learning, including automated testing, model deployment, and version control
Deploy ML models as scalable APIs and microservices meeting clinical performance and latency requirements
Implement monitoring for model performance, data drift, and system health in production
Develop and optimize ETL processes transforming healthcare data, including FHIR and HL7, for model training and inference
Help build and maintain feature stores and data layers for consistency between training and production
Integrate ML outputs into core healthcare applications with backend teams
Write clean, maintainable, and documented Python code
Participate in code reviews
Use Docker and Kubernetes to package and orchestrate ML workloads
Follow protocols for HIPAA and HITRUST-compliant data handling and deployments
Travel up to 10% domestically as needed
Attend company on-site onboarding during the initial days of employment

Requirements

What you’ll need

Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Engineering
4 years of professional experience in software engineering or data engineering, with 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
2 years of hands-on experience with containerization using Docker
2 years of experience with ML libraries such as PyTorch or Scikit-learn
2 years of experience with MLOps tools such as Airflow, Prefect, BentoML, or Kubeflow
2 years of experience with data processing frameworks such as Pandas, Spark, or dbt
Must be legally authorized to work in the country of employment without sponsorship for employment visa status

Benefits

Comp & perks

Medical, Dental & Vision
Health Savings Accounts
Health Care & Dependent Care Flexible Spending Accounts
Disability Benefits
Life Insurance
Voluntary Benefits
Paid Absences
Retirement Benefits
Company-paid travel arrangements and related expenses for on-site onboarding