IN_Senior Associate_ML Ops Lead_GCC_Advisory_Bangalore

Job Description & Summary

*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.

Mandatory skill sets

• Python, Machine learning , Deep learning

Years of experience required

Education qualification

• Full time B. E
• Education (if blank, degree and/or field of study not specified)
• Certifications (if blank, certifications not specified)

Optional Skills

• Desired Languages (If blank, desired languages not specified)