Role : MLOps Architect
About Modak
Modak is a fast-growing boutique data engineering firm that enables enterprises to manage and utilize their data landscape effectively. Modak uses machine learning (ML) techniques to transform how analytics content is prepared, consumed, and shared. Modak Nabu has been featured in multiple Gartner reports, including Market guide for Active Metadata Management, and Market guide for Data and Analytics Governance Platforms
Job Description
Hiring an experienced MLOps Architect with hands-on expertise in building scalable ML pipelines for enterprise environments. This role demands leadership in architectural decisions and deep proficiency in AWS-based tools to drive MLOps adoption across data science and engineering teams.
Key Responsibilities
- Design secure, scalable MLOps architectures using patterns like CI/CD for ML, model versioning, and automated deployments aligned with cloud-native principles.
- Lead implementation of MLOps frameworks with tools such as MLflow for experiment tracking, Databricks for collaborative ML workflows, and Azure ML for end-to-end lifecycle management.
- Drive platform adoption by aligning data science needs with engineering through solution blueprints, POCs, and cross-functional collaboration.
- Architect and optimize Azure services including DevOps pipelines, Data Factory for ETL orchestration, and ML services for monitoring model performance in Qualifications :
- 7+ years in MLOps or ML engineering, with proven hands-on work in MLOps frameworks, MLflow, and Databricks.
- 3+ years in solution architecture or technical product ownership, including leading architectural decisions and enterprise platform rollouts.
- Strong expertise in Azure ecosystem (DevOps, AWS ML, Data Factory) and designing reusable patterns for secure, scalable ML systems.
- Experience bridging data science and engineering via clear designs, plus familiarity with Python/SQL for pipeline development.
(ref:hirist.tech)
