ML Engineer (Healthcare)

Location: Remote in Pennsylvania, United States. Up to 10% domestic travel may be required, including company-paid onsite onboarding during the initial days of employment.

Company

hirify.global is a healthcare company developing solutions at the intersection of health, material, and data science.

What you will do

• 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 for clinical use, meeting performance and latency requirements.
• Implement monitoring for model performance, data drift, and production system health.
• Develop ETL pipelines that transform FHIR and HL7 healthcare data into datasets for training and inference.
• Maintain feature stores and data layers, and integrate ML outputs into healthcare applications with backend teams.
• Write maintainable Python code, use Docker and Kubernetes, and support secure, compliant deployments.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Engineering, or a related field.
• 3–5 years of professional software or data engineering experience, including at least 2 years focused on machine learning production environments.
• Strong Python skills and familiarity with SQL.
• Experience with AWS, Azure, or GCP and Docker.
• Familiarity with PyTorch or Scikit-learn, plus MLOps tools such as Airflow, Prefect, BentoML, or Kubeflow.
• Experience with Pandas, Spark, or dbt, and compliance with HIPAA and HITRUST security standards. Must be legally authorized to work in the United States without employment visa sponsorship.

Nice to have

• Experience deploying LLMs or using LangChain.
• Experience in a regulated industry such as healthcare or finance.
• Understanding of API design and microservices architecture.
• Knowledge of a compiled language such as Go or Java.

Culture & Benefits

• Work remotely with occasional domestic travel.
• Company-paid travel and expenses for initial onsite onboarding.
• Programs supporting physical and financial well-being.
• Corporate policies, procedures, and security standards support professional and compliant work.