Job Description :

- Design, implement, and manage MLOps workflows, tools, and operational processes for AIML solutions.

- Oversee the day-to-day stability, reliability, and operational health of ML models and ML pipelines.

- Manage model lifecycle operations, model registration.

Experience and Skills :

- Experience with MLOps tools and cloud ML platforms such as MLflow, Databricks, Azure ML, or equivalent.

- Familiarity with dashboards and alerting tools such as Power BI, Tableau, Databricks SQL dashboards.

Key Responsibilities :

- Architect and deploy robust machine learning pipelines to automate data processing and model training for large-scale enterprise applications.

- Collaborate with engineering teams to integrate AI models into production environments, ensuring high availability and performance.

- Optimize existing algorithms to improve predictive accuracy and reduce latency, directly impacting the quality of customer-facing insights.

- Mentor junior engineers and conduct code reviews to maintain high standards of technical excellence and best practices across the development lifecycle.

- Partner with business units to identify opportunities for AI implementation, translating business requirements into technical specifications that deliver measurable ROI.