TL;DR
Project Manager (AI): Owns quality assurance, workforce planning, and training programs for AI training data delivery on multiple small projects or one large strategic project with an accent on performance, compliance, and processes across multiple projects. Focus on coaching Coordinators and Associate PMs on QA, workflows, and tools; supporting onboarding and skills growth.
Location: Remote
Company
Welo Data works with technology companies to provide datasets that are high-quality, ethically sourced, relevant, diverse, and scalable to supercharge their AI models.
What you will do
- Monitor QA plans in partnership with the Quality team, tracking risks of defects and leading corrective actions.
- Forecast capacity needs, schedule shifts, and align vendors and internal teams to meet volume and turnaround targets.
- Build and deliver training and certification for raters/annotators and coordinators, updating materials as guidelines change.
- Maintain dashboards for throughput, quality, productivity, and cost, turning data into clear actions for improvement.
- Ensure policy adherence on data handling, privacy, safety, and platform access, supporting audits and remediation.
- Coach Coordinators and Associate PMs on QA, workflows, and tools, supporting onboarding and skills growth.
Requirements
- Bachelor’s degree or equivalent experience in business, data/operations, engineering, or related fields.
- 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.
- Clear communication with clients and internal partners, confident in reviews and governance forums.
- Solid use of spreadsheets, PM/task boards, and basic BI.
- Comfortable working with global, distributed teams (intermediate to advanced English).
Nice to have
- 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.
Culture & Benefits
- Practical, applied AI expertise to projects.
- Strong academic experience and a deep working knowledge of state-of-the-art AI tools, frameworks, and best practices.