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IQVIA

AI/ML Architect, MediaOS Platform

IQVIA

AI/ML Architect defining and leading intelligent capabilities within MediaOS platform at IQVIA. Collaborating cross-functionally to embed advanced AI-driven decisioning into a scalable platform.

Posted 6/12/2026full-timeAustin • North Carolina, Texas • 🇺🇸 United StatesSeniorLead💰 $103,300 - $287,600 per yearWebsite

Tech Stack

Tools & technologies
AWSAzureCloudDistributed SystemsGoogle Cloud PlatformJavaPythonPyTorchScalaScikit-LearnTensorflow

About the role

Key responsibilities & impact
  • Architect and design end-to-end AI/ML solutions for the MediaOS platform
  • Define and implement scalable ML pipelines, including data ingestion, feature engineering, model training, deployment, and monitoring
  • Lead the design of cloud-native, distributed AI systems leveraging modern frameworks and high-performance computing environments
  • Partner with product, data engineering, and platform teams to translate business requirements into robust AI-driven solutions
  • Establish and enforce MLOps best practices, including CI/CD, model versioning, observability, governance, and lifecycle management
  • Evaluate and integrate emerging AI technologies, including Generative AI, LLMs, and NLP applications where applicable
  • Drive data strategy alignment, ensuring high-quality, well-governed datasets to support model development and scalability
  • Mentor and guide engineers and data scientists, fostering a culture of innovation, collaboration, and technical excellence
  • Architect secure AI platforms, including authentication and authorization models (e.g., RBAC, ABAC)

Requirements

What you’ll need
  • 8+ years of experience in AI/ML, Data Science, or related fields
  • Proven track record of designing and deploying production-grade ML systems at scale
  • Strong programming expertise in Python (preferred) and/or Java/Scala
  • Hands-on experience with ML frameworks such as TensorFlow, PyTorch, Scikit-learn
  • Deep understanding of data architecture, distributed systems, and cloud platforms (AWS, Azure, or GCP)
  • Experience with real-time and batch processing systems
  • Strong knowledge of MLOps tools, frameworks, and lifecycle practices
  • Experience designing secure AI systems, including authentication and authorization frameworks (RBAC, ABAC)

Benefits

Comp & perks
  • Cutting-edge technology
  • Flexible work environment
  • Leadership opportunity

ATS Keywords

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Hard Skills & Tools
AI/ML solutionsML pipelinesdata ingestionfeature engineeringmodel trainingmodel deploymentmodel monitoringMLOpsprogramming in Pythonprogramming in Java
Soft Skills
leadershipmentoringcollaborationinnovationtechnical excellence