Wipro Limited (NYSE: WIT, BSE: 507685, NSE: WIPRO) is a leading technology services and consulting company focused on building innovative solutions that address clients’ most complex digital transformation needs. Leveraging our holistic portfolio of capabilities in consulting, design, engineering, and operations, we help clients realize their boldest ambitions and build future-ready, sustainable businesses. With over 230,000 employees and business partners across 65 countries, we deliver on the promise of helping our customers, colleagues, and communities thrive in an ever-changing world. For additional information, visit us at www.wipro.com.
The purpose of this role is to increase revenue, maximize process efficiency & cost-effectiveness, and ensure excellent customer experience, through effective supervision of daily operations and personnel, contract compliance, resource optimization and capability development within an account.
Demonstrated ability to analyze large volumes of operational data to identify defect trends, calculate key performance metrics (such as Inter-Rater Reliability, precision, and recall), and make evidence-based decisions to improve overall dataset health.
Proven expertise in systematically investigating quality regressions. The candidate must be able to trace errors back to their origin—whether stemming from tool limitations, policy ambiguity, or human error—and implement effective Corrective and Preventive Actions (CAPA).
Strong verbal and written communication skills required to bridge the gap between technical and non-technical teams. The candidate must be capable of presenting complex quality reports to engineering stakeholders while providing clear, actionable feedback to operational workforces.
Experience developing, implementing, and maintaining rigorous audit frameworks and Standard Operating Procedures (SOPs). The ability to define statistically significant sampling strategies that balance rigorous quality checks with operational throughput.
The ability to lead regular calibration sessions to align multi-tiered teams on subjective guidelines. Must possess the coaching skills necessary to design structured feedback loops that effectively correct annotator behavior and reduce recurring defect rates.
The Quality Lead is responsible for defining, measuring, and upholding the data integrity standards for machine learning annotation workflows. This role involves designing robust quality assurance (QA) frameworks, managing team performance metrics, and driving continuous improvement initiatives. The ideal candidate will act as the final gatekeeper for data accuracy, ensuring that all deliverables meet strict engineering thresholds before model training.
Key Competencies and Responsibilities:
Quality Assurance & Audit Frameworks:
Design and manage statistical sampling strategies to evaluate large-scale annotation datasets. Oversee the daily operations of QA auditors to ensure rigorous, unbiased reviews of ground-truth data.
Metrics Tracking & Reporting:
Monitor, analyze, and report on primary quality metrics, including Inter-Rater Reliability (IRR), precision, recall, and overall defect rates. Develop and maintain dashboards to provide ongoing visibility to cross-functional stakeholders.
Root Cause Analysis (RCA):
Lead deep-dive investigations into quality regressions or sudden drops in annotator performance. Identify whether errors stem from tooling defects, ambiguous policy documentation, or operational oversight, and implement corrective actions.
Feedback Loops & Calibration:
Establish structured, actionable feedback mechanisms for the annotation workforce to correct behavioral trends and reduce recurring errors. Lead regular calibration sessions with Policy Leads and Engineering to align on quality definitions and subjective edge cases.
Process Optimization:
Identify bottlenecks in the QA workflow and collaborate with operational managers to streamline auditing processes, ensuring high-quality output without severely impacting overall throughput.
Core Qualifications:
Proven experience in quality management, data operations, or a highly analytical QA role.
Strong proficiency in statistical analysis, data sampling methodologies, and identifying defect trends.
Detail-oriented mindset with the ability to communicate complex quality issues clearly to both technical and non-technical teams.
Practical experience with, or formal certification in, continuous improvement methodologies such as Lean, Six Sigma (Green Belt or above), or Kaizen,
Prior exposure to industry-standard data annotation platforms and an understanding of how tool design, hotkeys, and user interface ergonomics directly impact annotator fatigue and error rates.
Mandatory Skills: Geographic Information Systems(Maps) .
Experience: 5-8 Years .
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Wipro Limited (NYSE: WIT, BSE: 507685, NSE: WIPRO) is a leading AI-powered technology services and consulting company focused on building innovative solutions that address clients’ most complex digital transformation needs. Leveraging our consulting-led approach and the Wipro Intelligence™ unified suite of AI-powered platforms, solutions and transformative offerings, we help clients realize their boldest ambitions to build intelligent and sustainable businesses. The Wipro Innovation Network – part of the Wipro Intelligence™ suite – underpins our commitment to client-centric co-innovation and co-creation by bringing together capabilities from the innovation labs and partner labs, academia, and global tech communities. With over 240,000 employees and business partners across 65 countries, we deliver on the promise of helping our customers, colleagues, and communities thrive in an ever-changing world. For additional information, visit us at www.wipro.com.