Join Iris Software, a rapidly growing IT services company recognized as one of India's Top Best Workplaces in the IT industry. We are seeking a seasoned MLOps Lead to define and drive our enterprise MLOps strategy. This is an opportunity to shape the future of AI and machine learning operations within an award-winning culture that values talent and ambition.

At Iris, we are dedicated to being our clients' most trusted technology partner. With a global presence and expertise across various industries, we focus on complex, mission-critical applications using cutting-edge technologies. Our vision is to empower our associates to realize their full potential through ownership and growth.

As an MLOps Lead, you will be instrumental in defining and implementing enterprise MLOps strategy, aligning with organizational AI and machine learning objectives. This includes establishing governance frameworks, engineering standards, and deployment best practices.

You will lead the design of CI/CD architectures for automated machine learning lifecycles, define enterprise standards for model deployment, serving, and operational management, and set governance for model registry, versioning, and traceability. Your role will involve driving automation to accelerate deployments and ensure release consistency. You will also define standards for model monitoring, drift detection, and retraining to maintain long-term production model effectiveness. Leading architecture reviews and guiding teams on MLOps best practices will be key, alongside identifying and mitigating deployment risks and governance gaps. Collaboration with stakeholders to align MLOps initiatives with business goals and driving continuous improvement will be essential.

This role requires 8-10 years of experience with mandatory skills in Machine Learning (ML), CI/CD for ML pipelines, Model Deployment & Serving, Model Lifecycle Management, Model Registry & Experiment Tracking, and Python.

Additional expertise in Advanced GenAI & Agentic Framework Concepts, NLP, PyTorch, and Databricks is advantageous. You should demonstrate strong leadership, accountability, and strategic thinking, with the ability to collaborate effectively and communicate complex MLOps strategies. A customer-centric mindset and a proactive approach to engineering governance and operational excellence are also critical.