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
Job Reference: #LI-JC1
Role Purpose
Manages complex, strategic AI training data projects. Owns end-to-end delivery, client relationships, and financial outcomes. Guides Project Coordinators, executes quality strategy in partnership with quality team, and drives process improvements and new service pilots. Assists in the management of complex projects that enable Generative AI capabilities for clients, guiding project coordinators and partnering with Quality on standards and continuous improvement.
Key Responsibilities
- Program & Delivery Leadership: Execute delivery plans, milestones, resourcing, and controls for large or multi-workstream AI data projects (collection, labeling, evaluation).
- Client Management: Contribute to regular governance, status, and planning sessions; handle scope, priorities, and change.
- Financial Ownership: Track budgets, rates, and margins; manage forecasts, burn, and change orders to protect profitability.
- Quality Partnership: Share accountability with the Quality Analyst team for QA approach and continuous improvement loops.
- Resource & Capacity Planning: Plan and secure rater/annotator capacity; align training, shifts, and handoffs across time zones.
- Risk, Issue & Change Control: Run root-cause and corrective actions; escalate material risks with options and impact.
- Process & Service Innovation: Contribute to SOPs, templates, and dashboards; pilot new delivery methods and services for AI data programs.
- Compliance & Security: Ensure data handling, privacy, and security policies are followed across all workstreams.
- Reporting & Insights: Keep trackers and dashboards current; translate delivery data into clear, actionable insights for clients and leaders.
Requirements
Education
- Bachelor’s degree or equivalent experience in business, data/operations, engineering, or related fields
Experience
- 1+ years leading complex project delivery or operations (AI data, content review, annotation, labeling, or adjacent domains)
- Experience coordinating multi-team delivery and managing client touchpoints
Skills
- Strong planning and organization across parallel workstreams
- Clear written and spoken communication with senior client stakeholders
- Solid use of spreadsheets, PM/task boards, and basic BI; comfort with ETL concepts is a plus
- Quality mindset with practical use of SOPs, QA gates, and acceptance criteria
- Financial awareness (budgets, margin, change orders) and sound trade-off judgment
- Coaching ability for junior PMs and Coordinators
- Confident escalation and negotiation to resolve risks, issues, and scope questions
- Comfortable working with global, distributed teams (intermediate to advanced English)
Additional Qualifications (P1+)
- 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
Scope & Autonomy (P1 Alignment)
- Assists in leading one large strategic project or several medium projects end-to-end
- Executes delivery approach within scope, budget, and policies; escalates only non-standard or high-impact items
- Provides day-to-day direction to a small delivery pod (e.g., 2–8 Junior PMs/Coordinators) and influences cross-functional partners
- Shares accountability for quality outcomes with the Quality Analyst.
Skills Required
- Bachelor's degree or equivalent experience in business, data or operations, engineering, or a related field
- At least 1 year leading complex project delivery or operations
- Experience in AI data, content review, annotation, labeling, or an adjacent domain
- Experience coordinating multi-team delivery and managing client touchpoints
- Strong planning and organization across parallel workstreams
- Clear written and spoken communication with senior client stakeholders
- Experience using spreadsheets, project management or task boards, and basic business intelligence tools
- Quality-focused experience with SOPs, QA gates, and acceptance criteria
- Financial awareness covering budgets, margins, forecasts, and change orders
- Ability to coach junior project managers and coordinators
- Ability to escalate and negotiate risks, issues, and scope questions
- Comfort working with global distributed teams and intermediate to advanced English
- Near-native English with strong writing and editorial skills
- Hands-on experience with generative AI tools for text, voice, or video
- Background in QA testing, rubric design, or AI safety and ethics evaluation
- Familiarity with data annotation platforms and model evaluation tools
- Ability to interpret code, datasets, and system workflows conceptually
- Ability to work independently and manage workflows in a remote environment
- Multilingual ability beyond English
