Job Overview
Location
Gurgaon, India
Job Type
Full-time
Category
Software Engineering
Date Posted
May 23, 2026
Full Job Description
đź“‹ Description
- • Oversees a portfolio of multi-project Generative AI data operations programs, ensuring end-to-end delivery and scalable execution across global linguistic and cultural contexts.
- • Leads capacity planning for AI training data initiatives, aligning workforce scale with project demands across 300+ languages and locales supported by a global network of 500,000+ vetted experts.
- • Manages relationships with external vendors and data contributors, ensuring timely delivery of high-quality multilingual datasets for LLMs, voice/speech systems, agentic workflows, and embodied AI applications.
- • Implements and optimizes process automation workflows to improve efficiency, reduce manual overhead, and maintain consistency in data production across modalities and domains.
- • Ensures consistent quality standards across all data programs by collaborating closely with the Sr. Quality Analyst to define, monitor, and refine evaluation rubrics and calibration protocols.
- • Applies NIMO™ (Network Identity Management and Operations) framework to maintain data integrity, prevent fraud, and ensure traceability of all contributor-sourced data within the global workforce.
- • Monitors program performance metrics and drives continuous improvement initiatives to enhance accuracy, cultural relevance, and safety of AI training datasets.
- • Coordinates cross-functionally with technical, quality, and operations teams to align data production timelines with AI model development cycles from training through deployment.
- • Designs and executes localized quality assurance strategies tailored to regional linguistic nuances, dialects, and cultural contexts to mitigate bias and enhance inclusivity in AI outputs.
- • Tracks and reports on key operational KPIs including throughput, error rates, contributor compliance, and turnaround times to inform strategic scaling decisions.
- • Supports the development and implementation of standardized operating procedures for multilingual data creation and model evaluation across diverse AI applications.
- • Ensures all data operations comply with global data governance standards and uphold the integrity of Welo Data’s proprietary evaluation systems.
- • Participates in planning and resource allocation for new AI use cases, translating technical requirements into actionable data operations roadmaps.
- • Maintains awareness of emerging trends in Generative AI and multilingual data needs to proactively adapt operational strategies and workforce capabilities.
🎯 Requirements
- • Proven experience managing portfolios of AI training data or machine learning data operations programs
- • Demonstrated expertise in vendor management and scaling global, distributed workforces for data collection and annotation
- • Strong understanding of Generative AI applications including LLMs, voice/speech systems, and agentic workflows
- • Experience implementing process automation and operational efficiency improvements in data production environments
🏖️ Benefits
- • Opportunity to work at the forefront of multilingual Generative AI development with global impact
- • Access to proprietary NIMO™ fraud-prevention and identity verification technology
- • Exposure to cutting-edge AI models and evaluation frameworks across 300+ languages
- • Collaboration with a network of 500,000+ vetted linguistic and cultural experts worldwide
Skills & Technologies
About WeLoglobal Inc.
WeLoglobal is a technology company specializing in providing innovative logistics and supply chain solutions. Their platform leverages advanced analytics, AI, and automation to optimize transportation, warehousing, and inventory management for businesses across various industries. WeLoglobal aims to enhance efficiency, reduce costs, and improve visibility throughout the supply chain. They offer services such as freight management, last-mile delivery optimization, and real-time tracking, enabling clients to streamline their operations and meet customer demands more effectively. The company focuses on digital transformation within the logistics sector, making complex supply chains more manageable and responsive.
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