IN_Senior Associate_ML Ops Lead_GCC_Advisory_Bangalore

Job Description & Summary

A career withinData & AnalyticsServices will provide you with the opportunity to help our clientsleveragetransformation 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-nativeMLOpspipelines for training, validation, deployment, and lifecycle management.

• Develop and manage ML infrastructureonAzure, 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 withdata scientists, engineers, and stakeholders to deliver scalable ML systems.

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

• Mentor teams onMLOpspractices, cloud engineering, and designing production-grade ML systems.

• Stayup-to-datewith evolving trends inMLOps, 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.

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

• Demonstrated success taking models from experimentation through to production usingMLOpsbest 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 withhealthcarerevenue cycle, is a plus.

Preferred skill sets:

Python, Machinelearning ,Deep learning

Years of experience required:

8+years

EmploymentType :Full Time, Permanent

Education qualification:

Full timeB.E