What are the responsibilities and job description for the Senior Lead AI/MLOps Engineer - Pleasanton, CA (Local Candidate) position at Metalight Solutions Inc?
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