IN_Senior Associate_ML Ops Lead_GCC_Advisory_Bangalore

Job Description & Summary 

A career within Data & Analytics Services will provide you with the opportunity to help our clients leverage transformation to enhance their customer experiences. 

*Responsibilities:  

Position Overview: ML Ops Lead 

• Lead the full ML system lifecycle: from experimentation and model development to production deployment and ongoing monitoring. 

• Design and build scalable, cloud-native MLOps pipelines for training, validation, deployment, and lifecycle management. 

• Develop and manage ML infrastructure on Azure, with emphasis on Azure Kubernetes Service (AKS). 

• Implement best practices for model versioning, CI/CD, observability, and reproducibility in ML workflows. 

• Productionize ML models as robust, low-latency APIs and batch systems integrated into healthcare workflows. 

• Collaborate cross-functionally with data scientists, engineers, and stakeholders to deliver scalable ML systems. 

• Monitor model performance, detect drift, and ensure continuous model improvement in production. 

• Mentor teams on MLOps practices, cloud engineering, and designing production-grade ML systems. 

• Stay up-to-date with evolving trends in MLOps, distributed systems, and the Azure AI ecosystem. 

Who We Are Looking For: 

• 8+ years of experience in Machine Learning Engineering, MLOps, Data Science, or related quantitative fields. 

• Strong background in machine learning complemented by software engineering skills and systems thinking for production deployments. 

• Proven experience with large-scale, high-dimensional datasets and building scalable, reliable ML pipelines. 

• Expertise with modern ML methods, including Transformers for NLP and representation learning. 

• Demonstrated success taking models from experimentation through to production using MLOps best practices (CI/CD, automation, orchestration). 

• Ability to independently own ambiguous problems and deliver end-to-end ML solutions. 

• Excellent collaboration, communication, and stakeholder management skills. 

• Hands-on experience deploying, monitoring, and managing ML models in cloud environments, preferably Azure and AKS. 

• Healthcare domain experience, particularly with healthcare revenue cycle, is a plus. 

Preferred skill sets:   

Python, Machine learning , Deep learning  

Years of experience required:   

8+ years 

Employment Type : Full Time, Permanent 

Education qualification:   

Full time B. E