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
Role Purpose
Owns quality assurance, workforce planning, and training programs for AI training data delivery on multiple small projects or one large strategic project. Improves performance, compliance, and processes across multiple projects. Partners with the Senior Quality Analyst to share accountability for client outcomes and team performance. “Owns quality, workforce, and training programs that scale Generative AI data operations, driving performance, compliance, and process improvement across a project.
Key Responsibilities
· Quality Assurance: Monitor QA plans in partnership with Quality team (sampling, audits, acceptance criteria). Track risks of defects, lead corrective actions, and prevent recurrences.
· Workforce Planning: Forecast capacity needs; schedule shifts and handoffs; align vendors and internal teams to meet volume and turnaround targets.
· Training Programs: Build and deliver training and certification for raters/annotators and coordinators; update materials as guidelines change.
· Performance Management: Maintain dashboards for throughput, quality, productivity, and cost; turn data into clear actions for improvement.
· Compliance & Security: Ensure policy adherence on data handling, privacy, safety, and platform access; support audits and remediation.
· Process Improvement: Standardize SOPs and checklists; remove bottlenecks; pilot small changes that improve speed, quality, or cost.
· Stakeholder & Client Support: Join client reviews with the Quality Manager and PMs; explain quality results, risks, and next steps.
· Team Development: Coach Coordinators (C2–C3) and Associate PMs (P1) on QA, workflows, and tools; support onboarding and skills growth.
· Risk & Change Control: Keep risk/issue logs; manage change requests that impact quality, capacity, or training; escalate high-impact items with options.
Requirements
Education
Bachelor’s degree or equivalent experience in business, data/operations, engineering, or related fields
Experience
· 2+ years in project/operations delivery with hands-on QA and workforce planning (AI data, content review, labeling/annotation, or adjacent domains)
· Experience running trainings and coordinating multi-team delivery
Skills
· Planning and organization across multiple projects (quality, workforce, and training tracks)
· Clear communication with clients and internal partners; confident in reviews and governance forums
· Solid use of spreadsheets, PM/task boards, and basic BI; familiarity with ETL concepts is a plus
· Practical QA know-how (sampling, audits, acceptance criteria) and continuous-improvement mindset
· Capacity planning, scheduling, and vendor coordination
· Coaching for C2–C3 Coordinators and P1s; gives day-to-day guidance
· Confident escalation and negotiation to resolve risks, issues, and scope questions
· Comfortable working with global, distributed teams (intermediate to advanced English).
Additional Qualifications
· Near-native English with strong writing and editorial skills
· Hands-on experience with generative AI tools (text, voice, or video)
· Background in QA testing, rubric design, or AI safety/ethics evaluation
· Familiarity with data-annotation platforms and model-evaluation tools
· Ability to interpret code, datasets, and system workflows at a conceptual level (no coding required)
· Able to work independently and manage workflows effectively in a remote environment
· Multilingual ability beyond English.
