Komen Graduate Training Program UT MDACC · 18 hours ago
Machine Learning Engineer - Platforms
United States
Full-time
Remote
Mid Level
$123K/yr - $185K/yr
3+ years expKomen Graduate Training Program UT MDACC is focused on developing AI solutions to improve patient care and advance research. The Machine Learning Engineer - Platforms role is responsible for building and maintaining the enterprise AI/ML platform, ensuring its reliability and scalability while collaborating with data scientists and IT teams for effective AI deployment.
Hospital & Health Care
No H1B
Responsibilities
Support development, administration, and maintenance of the enterprise AI/ML platform (Dataiku, Kubernetes, Azure), ensuring scalability, reliability, and smooth integration with institutional systems
Orchestrate training, deployment, and inference pipelines within Dataiku targeting Azure and on-premises Kubernetes clusters
Develop and maintain MLOps workflows for reproducibility, version control, governance, and model lifecycle management
Manage and optimize containerized environments using Docker and Kubernetes to support data science workloads
Provide platform support for data scientists and ML engineers, troubleshooting environment, pipeline, and dependency issues
Monitor platform performance, cost, security, and compliance, ensuring alignment with enterprise and regulatory standards
Build and support scalable pipelines in Dataiku, Kubernetes, and Azure, including feature engineering, model tracking, and validation workflows
Debug, test, and resolve complex platform or pipeline issues using strong analytical and problem-solving skills
Assist with healthcare data integration using standards such as HL7, FHIR, or DICOM when required for model development
Share platform knowledge, best practices, and methodologies through training, documentation, and cross-team collaboration
Support analytics and automation workflows by enabling access to data, reviewing project requests, and assisting with interpretation
Communicate platform updates, risks, performance, and issue resolutions clearly during meetings and collaborative sessions
Work effectively with leaders, technical peers, and end users, ensuring strong communication across both technical and non-technical stakeholders
Perform additional tasks as assigned to support the AI/ML platform, MLOps practices, and enterprise data science initiatives
Qualification
Required
Bachelor's Degree Computer Science, Software Engineering, Data Science, Physics, Math & Statistics, or another related engineering discipline
3 years in machine learning engineering, data science, data engineering, and/or software engineering experience
1 year experience with Master's degree
No experience required with PhD
Preferred
Master's Degree Computer Science, Software Engineering, Data Science, Physics, Math & Statistics, or another related engineering discipline
Healthcare experience needed
Experience with MLOps platforms and/or cloud AI certifications
Strong proficiency in CI/CD and automation of the AI lifecycle
Experience working on healthcare focused machine learning projects
Experience with Azure and/or Kubernetes
Proficiency in services such as Azure Kubernetes Services and Azure ML (or similar)
Benefits
Paid medical benefits
Generous paid time off (PTO)
Strong retirement plans
Comprehensive benefits package designed to support your total well-being
Tuition benefits
Educational opportunities
Individual and team recognition
Company
Komen Graduate Training Program UT MDACC
Through generous funding from Susan G.
11-50 employees
Funding
Current Stage
Early StageCompany data provided by crunchbase