Machine Learning Engineer

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

📋 Description

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

• Implement ML models as scalable APIs and microservices that fulfill performance and latency standards for clinical applications.

• Establish monitoring for model performance, data drift, and the health of production systems.

• Create and enhance ETL processes that convert healthcare data, including FHIR and HL7, into datasets suitable for model training and inference.

• Assist in the development and maintenance of feature stores and data layers to ensure consistency between training and production settings.

• Collaborate with backend teams to integrate ML outputs into essential healthcare applications.

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

• Engage in code review processes.

• Utilize Docker and Kubernetes to package and manage ML workloads.

• Ensure that data handling and deployments comply with HIPAA and HITRUST security regulations.

• Be prepared for domestic travel up to 10%.

• Complete mandatory on-site onboarding during the initial days of employment.

⛳️ Requirements

• A Bachelor's degree or higher in Computer Science, Software Engineering, Data Engineering, or a related discipline.

• Over 6 years of professional experience in software engineering or data engineering.

• At least 5 years of experience with Python and a working knowledge of SQL.

• Minimum of 2 years in machine learning production environments.

• 5 years of experience with AWS and containerization (Docker).

• 3 years of experience in Java.

• 3 years of experience with ML libraries (such as PyTorch or Scikit-learn) and MLOps tools (including Airflow, Prefect, BentoML, or Kubeflow).

• 4 years of experience with data processing frameworks (like Pandas, Spark, or dbt).

• Familiarity with deploying Large Language Models (LLMs) or utilizing frameworks like LangChain.

• Experience in a regulated environment (Healthcare, Finance, etc.).

• Knowledge of API design and microservices architecture.

• Responsibilities must adhere to corporate policies, procedures, and security standards.

• Educational background and work history should be provided through a resume or application fields.

🏝️ Benefits

• Medical, Dental & Vision coverage.

• Health Savings Accounts.

• Flexible Spending Accounts for Health Care & Dependent Care.

• Disability Benefits.

• Life Insurance.

• Optional Benefits.

• Paid Time Off.

• Retirement Benefits.

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

• Domestic travel of up to 10% may be required.