ΠΡΠ° Π²Π°ΠΊΠ°Π½ΡΠΈΡ Π² Π°ΡΡ ΠΈΠ²Π΅
ΠΠΎΡΠΌΠΎΡΡΠ΅ΡΡ ΠΏΠΎΡ ΠΎΠΆΠΈΠ΅ Π²Π°ΠΊΠ°Π½ΡΠΈΠΈ β4 Π΄Π½Ρ Π½Π°Π·Π°Π΄
Machine Learning Engineer (Healthcare)
124Β 000 - 170Β 500$
ΠΠΏΠΈΡΠ°Π½ΠΈΠ΅ Π²Π°ΠΊΠ°Π½ΡΠΈΠΈ
Π’Π΅ΠΊΡΡ:
TL;DR
Machine Learning Engineer (MLOps/Healthcare): Building and maintaining production ML pipelines, APIs, and microservices for healthcare information systems with an accent on MLOps, data reliability, and secure cloud infrastructure. Focus on deploying and monitoring models, transforming FHIR and HL7 data, managing containerized workloads, and meeting HIPAA and HITRUST requirements.
Location: Remote within the United States; Pittsburgh, Pennsylvania is listed as the role location. Up to 10% domestic travel may be required, and on-site onboarding is required during the initial days of employment.
Salary: $124,000β$170,500 expected annual compensation, including base pay and variable incentive pay if eligible.
Company
develops healthcare solutions at the intersection of health, material, and data science, supporting healthcare professionals and patients.
What you will do
- Build and maintain CI/CD pipelines for machine learning, including automated testing, model deployment, and version control.
- Deploy machine learning models as scalable APIs and microservices and monitor performance, data drift, and production system health.
- Develop ETL pipelines that transform healthcare data in FHIR and HL7 formats for model training and inference.
- Maintain feature stores and data layers while integrating machine learning outputs into healthcare applications.
- Write documented Python code, participate in code reviews, and use Docker and Kubernetes to orchestrate ML workloads.
- Apply security and compliance practices aligned with HIPAA and HITRUST standards.
Requirements
- Bachelorβs degree or higher in computer science, software engineering, data engineering, or a related field.
- 6+ years of professional software engineering or data engineering experience.
- 5 years of Python experience and familiarity with SQL.
- 2 years of experience in machine learning production environments.
- 5 years of AWS and Docker experience, plus 3 years of Java experience.
- Experience with PyTorch or Scikit-learn, MLOps tools, and data processing frameworks such as Pandas, Spark, or dbt.
Nice to have
- Experience deploying large language models or using LangChain.
- Experience in regulated industries such as healthcare or finance.
- Understanding of API design and microservices architecture.
Culture & Benefits
- Remote work with up to 10% domestic travel.
- Company-paid travel and expenses for required on-site onboarding.
- Potential eligibility for medical, dental, vision, HSA, FSA, disability, life insurance, paid absences, and retirement benefits.
- Work supporting the Health Information Systems business.