IN_Senior Associate_MLOps Lead_GCC_Advisory_Hyderabad
PwC India (company site, opens in a new tab)8+ yrsHyderabadOn-siteDirect career pageEst. 30–50 LPA
Posted 8h ago
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Job description
Structured overview of role & requirements
About This Role
- Lead the end-to-end lifecycle of ML systems covering experimentation, deployment, and monitoring with scalable, cloud-native MLOps pipelines on Azure.
- Develop, productionize, and manage ML infrastructure focusing on Azure Kubernetes Service (AKS) and implement best practices including CI/CD, model versioning, and reproducibility.
- Collaborate across teams to deliver robust, low-latency ML models as APIs or batch systems and mentor peers in MLOps, cloud engineering, and production-grade ML system design.
Minimum Requirements
- Minimum 8+ years of experience in Machine Learning Engineering, MLOps, Data Science or related fields.
- Bachelor of Engineering degree required.
- Strong hands-on experience with ML model deployment, monitoring, and management in cloud environments, preferably Azure and AKS.
- Preferred but not mandatory: Healthcare domain experience, especially healthcare revenue cycle.
Ideal Candidate Profile
- Experienced in taking ML models from experimentation to production using MLOps best practices like CI/CD, automation, and orchestration.
- Strong systems thinking combined with software engineering skills for building scalable and reliable ML pipelines on Azure cloud.
- Able to independently solve ambiguous ML problems and mentor teams on MLOps and cloud-native production ML systems.