Doran Jones Inc.Remote
AI Engineer (Data / ML Platform)
United States of America
Full Time
1 hour ago
H1B Sponsor Likely
Key skills
Data engineeringMachine learning infrastructureBuilding data pipelinesCloud platformsPythonData processing frameworksLarge-scale datasetsAPI architecturesHealthcare data experienceNLP pipelinesFeature storesModern data architecturesAIMachine LearningMLNLPData EngineeringData LakeSparkAirflowAWSAzureGCP
About this role
Doran Jones Inc. is a healthcare technology organization undergoing a major modernization of its legacy platforms and data infrastructure. They are seeking an AI Engineer (Data) to focus on building scalable data pipelines, enabling machine learning systems, and integrating AI capabilities into modern healthcare applications.
Responsibilities:
- Design and build scalable data pipelines that support machine learning and AI-driven applications
- Develop and maintain ML-ready data infrastructure across structured and unstructured healthcare datasets
- Implement data ingestion, transformation, and feature engineering pipelines
- Build services that expose ML models and AI capabilities to internal applications and APIs
- Work with engineering teams to integrate AI functionality into modernized healthcare platforms
- Help migrate legacy data architectures to cloud-native data platforms
- Implement best practices for data governance, data quality, and observability
- Collaborate with product and engineering teams to deliver AI-powered healthcare solutions
- Contribute to the development of ML pipelines, model deployment workflows, and AI platform tooling
Requirements:
- 5+ years of experience in data engineering, machine learning infrastructure, or AI platform engineering
- Strong experience building data pipelines and distributed data systems
- Proficiency in Python for data processing and ML workflows
- Experience working with cloud platforms (AWS, GCP, or Azure)
- Experience with data processing frameworks (Spark, Airflow, or similar)
- Familiarity with ML lifecycle tools and model deployment workflows
- Experience working with large-scale structured and unstructured datasets
- Understanding of API-based architectures and microservices
- Strong problem-solving skills and the ability to work in modern distributed systems
- Experience working with healthcare data platforms or regulated environments
- Exposure to LLMs, NLP pipelines, or AI-driven applications
- Experience with feature stores, vector databases, or ML platforms
- Familiarity with modern data lake/lakehouse architectures
- Experience integrating AI services into production applications
- Experience working in modernization or platform transformation initiatives