ML Ops Engineer, Wipro

Machine Learning Engineer, ML Ops Engineer
Karnataka, India, Bengaluru
January 2, 2026
Regular

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Job Description

As an ML Ops Engineer at Wipro, they support end-to-end production processes by ensuring consistent performance, resolving technical escalations, and strengthening the technical capabilities of production teams. The role involves monitoring operational metrics, troubleshooting client issues, managing SLAs, mentoring specialists, and enabling operational excellence across enterprise digital transformation initiatives.

Date Posted: December 1, 2025

Expiration Date: NA

Experience: 5–8 Years

Job ID: NA

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Primary Responsibilities

  • Control the daily production process by monitoring transactions and performance against the set standards in order to provide excellent service.
  • Keep an eye on the team dashboards, productivity and quality scores, make sure SLA compliance and operational efficiency are maintained.
  • Give the staff technical help, process instructions, and troubleshooting so they can perform better and also be able to quickly solve issues.
  • In a very clear and precise manner keep tracking, documenting, and managing client queries, resolutions, and escalations.
  • Always make sure that all the processes are following the standard operating procedures and the contractual SLAs very strictly.
  • Go through the call/query logs to discover patterns, stop recurring problems, and enhance the service delivery.
  • Use a professional manner when talking to clients, keep the business, pursue their feedback, and improve the customer satisfaction.
  • Take the lead in spotting potential problems, pushing forward the most critical issues, and working together with the top management for a quick solution.

Essential Qualifications

  • 5-8 years’ experience in MLOps, production support or technical operations.
  • Expertise in MS Azure MLOps environment hands-on.
  • Experience in dealing with technical escalations and production issues in SLA-driven environments.
  • Good knowledge of process governance, quality metrics, and performance dashboards.
  • Excellent troubleshooting, analytical, and documentation skills.
  • Ability to communicate, coordinate and manage stakeholders excellently.

Preferred Qualifications

  • Knowledge of supporting machine learning or AI-based production systems.
  • Understanding of enterprise digital transformation or large-scale IT services environments.
  • Experience in compliance, governance, and risk management in production operations.
  • Mentoring or leading technical support teams is a prior experience.

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