Project Specialist

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Appen

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 1996

🤖 Artificial Intelligence

🏢 Enterprise

Artificial Intelligence • Data • Enterprise

Appen is a company that specializes in providing high-quality, scalable datasets for AI models and applications. With over 25 years of experience, Appen supports the complete AI lifecycle by collecting, curating, fine-tuning, and monitoring data. Their platform is known for its flexibility, allowing enterprises to unlock the potential of their enterprise data through human-AI collaboration. Appen's global reach and expertise make them a trusted partner in accelerating the development and implementation of AI technologies across various industries.

📋 Description

• Coordinate assigned project workstreams - covering productivity, qualification, training, crowd communications, and QA - to ensure on-time delivery against execution standards • Deliver high-quality annotation and QA during POC and pilot phases to establish quality benchmarks and de-risk new client relationships from day one • Partner with Client Partners and Pilot Teams to validate quote assumptions, including time-per-task and quality requirements, before finalization • Analyze datasets to surface patterns, insights, and optimization opportunities that inform automation strategy and drive thought leadership content for customers • Support Project Managers and Client Partners as the AI expert point of contact across client meetings, workshops, QBRs, and status updates • Maintain version control and change communication protocols to ensure contributors are informed of guideline updates prior to launch and throughout production • Translate QA findings into targeted improvements to supporting materials, reducing recurring annotation errors and improving overall data quality • Provide data-backed findings and consultancy insight to strengthen Appen's advisory value during critical early project phases and ongoing client relationships

🎯 Requirements

• Proven experience coordinating or delivering data annotation, content evaluation, or AI training data projects in a structured delivery environment • Strong understanding of data quality principles, QA methodologies, and annotation workflows within GenAI or adjacent AI domains • Ability to create clear, accurate contributor-facing documentation including guidelines, FAQs, and cheatsheets under tight timelines • Experience supporting pilot or POC phases, including validating operational assumptions and establishing quality benchmarks • Demonstrated ability to analyse datasets, identify patterns, and translate findings into actionable insights or process improvements • Confident communicator with experience engaging cross-functional stakeholders, including client-facing participation in meetings, workshops, or reporting cycles • Disciplined approach to version control, update management, and change communication across distributed contributor teams • Comfortable operating across multiple concurrent workstreams with a high degree of ownership and attention to delivery standards

🏖️ Benefits

• medical, dental, and vision coverage • retirement plan options • paid time off