Language Quality Manager

About Welo Data

Welo Data, a Welo Global brand, is the multilingual data and evaluation partner for foundation labs and enterprises deploying GenAI systems globally. They deliver the human judgment, data infrastructure, and evaluation systems that ensure AI models perform reliably across languages, cultures, and real-world contexts, at every stage from training through deployment.  Its global network of 500,000+ vetted experts spans 300+ languages and locales, enabling high-quality multilingual data creation and structured model evaluation across the full spectrum of modern AI applications — from large language models and voice and speech systems to agentic workflows and robotics and embodied AI. This breadth of linguistic, cultural, and domain expertise enables Welo Data to address critical AI development challenges, including safety, bias, inclusivity, and cross-lingual reliability. A unified global operating model, led by specialized program and quality experts and grounded in assessment-driven talent selection, localized rubrics, and continuous calibration, ensures consistent performance across languages, domains, and modalities. Underpinning all of this is NIMO™ (Network Identity Management and Operations), Welo Data's proprietary identity and fraud-prevention framework. Built to maintain data integrity and workforce trust across a global contributor base, NIMO combines advanced verification, continuous monitoring, and structured QA to ensure every dataset is accurate, traceable, and culturally grounded. welodata.ai   

Overview

As a Language Quality Manager, you will support a key client by ensuring that localized content meets the highest linguistic, cultural, and quality standards. This role operates as part of a client-aligned, long-term engagement model, working closely with both client stakeholders and internal Welo Data teams.

You will collaborate with internal and external partners to oversee translation quality across multiple content types. The role requires the ability to work autonomously in a fast-paced, client-driven environment, communicate effectively with both technical and non-technical stakeholders, and continuously adapt to evolving tools, workflows, and client requirements.

 

Job Reference: #LI-JC1 

\nResponsibilities

• Own the linguistic quality (language, tone, cultural appropriateness) of all localized content delivered for the assigned client under the Welo Data dedicated workforce model.
• Act as a client-facing quality partner, aligning linguistic quality outcomes with client brand, voice, and product expectations.
• Define, develop, and maintain linguistic assets (glossaries, style guides, terminology databases) aligned with client standards.
• Perform Localization Quality Assurance (LQA) activities including testing, issue logging, triage, and resolution.
• Track critical issues and provide regular status updates.
• Review translated content across product, marketing, sales, and communications materials.
• Consolidate and deliver linguistic feedback to external translators and vendors.
• Support urgent or ad hoc translation and review requests when required.
• Provide quality feedback during and after live product launches.

Ideal Candidate background

• BA/BS in Linguistics, Translation, or a related discipline.
• Minimum of 4 years of experience in translation, editing, or linguistic review.
• Experience with Smartling
• Experience using Jira or similar bug-tracking tools.
• Familiarity with client products and platforms (e.g., SaaS or technology products).
• Fluency in additional languages is a plus.
• Understanding of Agile frameworks.
• Knowledge of the software development lifecycle.
• Excellent written and verbal communication skills.
• Strong attention to detail and quality focus.
• Ability to manage multiple priorities independently.

\n

Please mention the word **PEPS** and tag RMTkyLjI1My4yMDkuMTMz when applying to show you read the job post completely (#RMTkyLjI1My4yMDkuMTMz). This is a beta feature to avoid spam applicants. Companies can search these words to find applicants that read this and see they're human.