About the company
Appen is a leader in AI enablement for critical tasks such as model improvement, supervision, and evaluation. To do this we leverage our global crowd of over one million skilled contractors, speaking over 180 languages and dialects, representing 130 countries. In addition, we utilize the industry's most advanced AI-assisted data annotation platform to collect and label various types of data like images, text, speech, audio, and video. Our data is crucial for building and continuously improving the world's most innovative artificial intelligence systems and Appen is already trusted by the world's largest technology companies. Now with the explosion of interest in generative AI, Appen is helping leaders in automotive, financial services, retail, healthcare, and governments the confidence to deploy world-class AI products. At Appen, we are purpose driven. Our fundamental role in AI is to ensure all models are helpful, honest, and harmless, so we firmly believe in unlocking the power of AI to build a better world. We have a learn-it-all culture that values perspective, growth, and innovation. We are customer-obsessed, action-oriented, and celebrate winning together. At Appen, we are committed to creating an inclusive and diverse workplace. We are an equal opportunity employer that does not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Job Summary
About the role:
Appen is a leader in AI enablement for critical tasks such as model improvement, supervision, and evaluation. We leverage our global crowd of over one million skilled contractors, speaking over 180 languages and dialects, representing 130 countries. Our data is crucial for building and continuously improving the world's most innovative artificial intelligence systems, trusted by the world's largest technology companies.
This team sits at the centre of GenAI data delivery, ensuring high quality execution across complex, fast-moving programs. The work directly plays a pivotal role in the training, evaluation, and optimization of industry-leading AI models. You will lead the operational and technical execution of GenAI data projects, owning scope, timelines, quality, budget, and stakeholder alignment across internal and external teams.
Responsibilities:
šLead planning and execution of GenAI projects, ensuring clear scope, timelines, execution, and deliverables while maintaining client relationships. šDeliver projects on time and to defined quality benchmarks through disciplined operational management. šDrive accurate forecasting and proactive risk mitigation to protect delivery commitments. šAlign internal teams, contributors, and clients to ensure clarity of expectations and execution standards. šStrategically improve productivity and quality by identifying bottlenecks and applying data-driven operational decisions. šStrengthen stakeholder engagement through structured communication and transparent daily, weekly, and monthly reporting. šEstablish structured project closure practices, capturing lessons learned, iterating operating processes, and identifying future opportunities. šDrive thought leadership and increase scalability of delivery models by applying repeatable workflows and structured improvements to accelerate delivery while maintaining quality.
Requirements:
š4+ years of experience in project management, technical operations, or AI and ML data programs, ideally in high-volume data operations. šProven ability to manage multiple projects while upholding high delivery and quality standards. šFamiliarity with large language models or generative AI, with experience in data annotation or AI training data projects strongly preferred. šStrong planning, organisation, and stakeholder communication capability across technical and non-technical audiences. šDemonstrated risk management and forecasting discipline within project environments. šStrong data orientation, with the ability to interpret dashboards, identify bottlenecks, and make operational decisions based on metrics. šWorking knowledge of tools such as Excel or SQL, with basic coding or data skills preferred. šProject Management qualification (PMP) or equivalent certification from Udemy, Coursera, or Google.
Nice-to-have: šBachelor's degree in a related field such as Economics, Business, Computer Science, Linguistics, Engineering, or Data Science. Advanced degree a plus.
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