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Strong PwC brand balanced by specialized Azure MLOps requirement reduces broad applicant density.
Role requires domain-specific ML Ops and cloud experience, limiting cross-industry transferability.
Explicit 6–10 years requirement and mandatory Azure ML Ops skill enforce strict filtering.
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Design, implement, and maintain scalable Azure ML Ops pipelines for machine learning deployment and operations.
Manage end-to-end deployment of ML models and optimize their performance and resource usage in production.
Collaborate with data scientists, engineers, and business stakeholders to integrate AI solutions aligning with organizational goals.
6–10 years of relevant experience specifically in machine learning operations with hands-on Azure ML Ops expertise.
Full-time onsite position based in Hyderabad with 100% resource allocation.
Mandatory proficiency in Azure ML Ops; AWS DevOps mentioned as required skill but context emphasizes Azure ML Ops.
Education: Preferred background in Computer Science, Data Science, Engineering or related fields; specifically Master or Bachelor of Engineering.
Experienced professional with deep technical capability in Azure ML Ops within data science and machine learning environments.
Skilled at managing ML deployment pipelines and optimizing operational processes in production settings.
Ability to work collaboratively with multi-disciplinary teams to achieve measurable business outcomes through AI solutions.