AI Engineer, Data / ML Platform
Doran Jones Inc.
full-time
Posted on:
Location Type: Remote
Location: Texas • United States
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About the role
- 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
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
data engineeringmachine learning infrastructureAI platform engineeringdata pipelinesdistributed data systemsPythoncloud platformsdata processing frameworksML lifecycle toolsAPI-based architectures
Soft Skills
problem-solvingcollaboration