MLOPs Engineer

Architect Skills

• 5 years in solution architecture or technical product ownership

• Has Iead architectural decisions and driven MLOPS platform adoption

• Expertise in designing secure, scalable, and reusable MLOPS architecture patterns aligned with enterprise cloud principles

• Strong experience with Azure (especially DevOps, ML services, Data Factory).

• Prior exposure to MLOps tooling (eg. Databricks, Azure, ML,MLFlow)

• Skilled at aligning data science and engineering through clear solution design

Scrum master Skills:

• Certified Scrum Master with 2+ years experience facilitating agile ceremonies and managing structured sprint execution.

• Experience in removing blockers and enabling cross-functional team collaboration.

• Experience in aligning sprint outcomes with product roadmap and driving continuous improvement

Soft Skill

• Coaching and mentoring skills to enable data science and engineering teams in using MLOPs tools and workflows effectively

• Experience supporting onboarding and scaling of use cases across business domains