Machine Learning Engineer

This is a fully remote position, open to applicants in Pennsylvania.

📋 Description

• Design and maintain CI/CD pipelines for machine learning, encompassing automated testing, model deployment, and version control.

• Deploy machine learning models as scalable APIs and microservices that meet clinical performance and latency standards.

• Establish monitoring systems for model performance, data drift, and overall system health in a production environment.

• Create and enhance ETL processes to transform healthcare data, including FHIR and HL7, for model training and inference.

• Assist in building and maintaining feature stores and data layers to ensure consistency between training and production environments.

• Collaborate with backend teams to integrate machine learning outputs into core healthcare applications.

• Write clean, maintainable, and well-documented Python code.

• Engage in code reviews to uphold quality standards.

• Utilize Docker and Kubernetes to package and orchestrate machine learning workloads.

• Adhere to protocols for HIPAA and HITRUST-compliant data handling and deployments.

• Travel up to 10% domestically as required.

• Participate in company on-site onboarding during the initial days of employment.

⛳️ Requirements

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or Data Engineering.

• Minimum of 4 years of professional experience in software engineering or data engineering, with at least 2 years dedicated to machine learning production environments.

• At least 2 years of experience in Python and SQL.

• Familiarity with a compiled language such as Go or Java.

• A minimum of 2 years of hands-on experience with at least one major cloud provider: AWS, Azure, or GCP.

• At least 2 years of practical experience with containerization using Docker.

• A minimum of 2 years of experience with machine learning libraries such as PyTorch or Scikit-learn.

• At least 2 years of experience with MLOps tools such as Airflow, Prefect, BentoML, or Kubeflow.

• A minimum of 2 years of experience with data processing frameworks like Pandas, Spark, or dbt.

• Must be legally authorized to work in the country of employment without needing sponsorship for a work visa status.

🏝️ Benefits

• Medical, Dental & Vision coverage.

• Health Savings Accounts.

• Flexible Spending Accounts for Health Care & Dependent Care.

• Disability Benefits.

• Life Insurance.

• Voluntary Benefits.

• Paid Absences.

• Retirement Benefits.

• Company-paid travel arrangements and related expenses for on-site onboarding.