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Senior Lead AI/MLOps Engineer - Pleasanton, CA (Local Candidate)

Metalight Solutions IncPleasanton, CA🇺🇸United StatesPosted 23 Jul 2026

Why This Role Stands Out

This hybrid role offers a fantastic opportunity to build and scale enterprise AI systems, leveraging cutting-edge Azure cloud platforms and Databricks. You'll thrive here if you're passionate about designing robust MLOps pipelines and deploying AI models in production, gaining valuable experience in a dynamic retail/e-commerce environment. Apply today to advance your career in AI/MLOps!

Quick Overview

Work Type
Hybrid
Level
Mid Senior

Job Description

About the Role

We are looking for a Senior AI / MLOps Engineer to build and scale enterprise AI systems. The role focuses on designing robust machine learning pipelines, deploying models in production, and leveraging cloud-based AI platforms for real-world business applications, especially in retail/e-commerce.

 

 Key Responsibilities

  • Design and implement end-to-end MLOps pipelines for ML lifecycle (build → deploy → monitor)
  • Build and manage CI/CD pipelines for AI/ML workloads
  • Develop scalable AI solutions on Azure cloud platform
  • Work extensively with Azure Databricks for data engineering, model training, and ML pipelines
  • Deploy applications on Azure Kubernetes Service (AKS)
  • Develop and enhance AI/ML models such as recommendation systems and forecasting models
  • Integrate Agentic AI tools (Copilot, Claude, etc.) into development workflows
  • Ensure production monitoring, reliability, and incident management
  • Collaborate with cross-functional teams for large-scale AI solution delivery

 

 Must-Have Skills

 MLOps / DevOps / CI-CD

  • Strong hands-on experience in MLOps frameworks and practices
  • Expertise in Azure Databricks (MLOps / pipelines / ML workflows)
  • Experience with:

Jenkins

GitHub Actions

CI/CD pipeline automation

 

 Azure Cloud Expertise

  • Strong experience in Azure ecosystem, including:
    • Azure Databricks
    • Azure Kubernetes Service (AKS)
    • Azure Storage & Monitoring

 

 AI / ML Capabilities

  • Experience with:
    • Recommendation systems
    • Forecasting models
  • Understanding of ML lifecycle from experimentation to production

 

 Agentic AI Tools

  • Practical exposure to:
    • Copilot
    • Claude or similar AI-assisted tools

 

 Production Support & Monitoring

  • Experience in:
    • Incident management
    • Monitoring tools (ServiceNow, PagerDuty, etc.)
  • Strong focus on production-grade deployments

 

 Good to Have

  • Experience in LLM / GenAI applications
  • Exposure to end-to-end AI pipelines using Databricks ecosystem
  • Knowledge of retail / e-commerce domain
  • Familiarity with scalable distributed data processing (Spark)

 

 Ideal Candidate Profile

  • Strong engineering mindset with hands-on experience in production AI systems
  • Deep understanding of Azure + Databricks + MLOps ecosystem
  • Ability to handle end-to-end ownership
  • Experience in enterprise-scale environments

 

 Summary

  • Core Focus: MLOps + Azure + Databricks + AI Engineering
  • Platform: Azure (AKS + Databricks + ML ecosystem)
  • Domain Preference: Retail / E-commerce

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