Overview
On Site
Depends on Experience
Full Time
Skills
PyTorch
Python
Vertex
Microsoft Azure
Retail
Machine Learning Operations (ML Ops)
Generative Artificial Intelligence (AI)
Data Engineering
Machine Learning (ML)
Artificial Intelligence
Computer Science
Job Details
About the job
Role is 100% On-Site in Houston, TX
5 Days per W/K.
Lead AI Engineer
We re seeking a Lead AI Engineer to architect and deliver enterprise-scale AI and machine learning solutions. This role blends hands-on model development with strategic technical leadership, guiding teams through the full AI lifecycle from data engineering to production deployment. Ideal candidates bring deep ML engineering and MLOps expertise, with retail or eCommerce experience strongly preferred.
Key Responsibilities
- Architect and deploy scalable AI/ML systems using Azure ML, SageMaker, or Vertex AI.
- Lead model development lifecycle: data ingestion, training, deployment, and monitoring.
- Mentor AI engineers, drive best practices, and advance MLOps maturity.
- Research and apply emerging methods including Generative AI, RAG, and agentic frameworks.
- Partner with cross-functional teams to turn business challenges into AI-driven solutions.
- Ensure model governance, reliability, and compliance with responsible AI standards.
- Collaborate with vendors to evaluate and integrate cutting-edge AI technologies.
Required Qualifications
- 5+ years in AI/ML engineering with hands-on model design and deployment.
- Proven technical leadership delivering production-grade AI systems.
- Proficiency in Python, TensorFlow, PyTorch, and Scikit-learn.
- Experience with cloud AI platforms, containerization, and CI/CD pipelines.
- Strong understanding of MLOps, data engineering, and model monitoring.
- Excellent communication and collaboration skills; ability to bridge tech and business.
- Bachelor s or Master s in Computer Science, AI, or Data Science.
Preferred Qualifications
- Retail or consumer analytics background.
- Experience with Generative AI, RAG pipelines, or agentic AI frameworks.
- Knowledge of data lakehouse architectures, governance, and responsible AI.
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