Machine Learning Architect II
Overview
Lead data science initiatives to transform large-scale data into actionable insights. Partner with cross-functional teams to deploy machine learning models into production using Docker containers and orchestrate workflows via CI/CD pipelines. Drive innovation by optimizing ML lifecycles on cloud platforms and mentor junior engineers.
What You'll Do8
- 1Model Deployment & Operationalization: Package models into Docker containers for scalable deployments on Kubernetes clusters
- 2Pipeline Automation: Build CI/CD pipelines using GitHub Actions for model training and deployment
- 3Cloud Infrastructure Management: Utilize Azure Container Registry and AKS for secure container image storage and scaling
- 4Monitoring & Maintenance: Implement observability solutions for tracking model performance and data drift in production
- 5Data Integration: Collaborate with data engineering teams to design Medallion architecture pipelines feeding into ML models
- 6Engineering Best Practices: Write modular Python code adhering to Git version control standards
- 7Mentorship: Guide junior MLOps engineers and lead career development initiatives
- 8Career Development: Conduct performance reviews and foster continuous learning across the organization
Requirements5
- 16+ years of MLOps or data engineering experience
- 23+ years managing MLOps/data platform teams with focus on mentorship
- 3Hands-on experience with Azure ML or Microsoft Fabric preferred
- 4Strong proficiency in Python for automation and deployment tasks
- 5Familiarity with Kubernetes, Docker, and CI/CD tools
Salary Insight
Salary not disclosed in listing
Location
Required Skills
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