Data Acquisition Director

What You'll Do

• Develop and execute data acquisition strategies to source high-quality, diverse datasets for AI training and evaluation
• Identify, evaluate, and negotiate with data providers, content partners, and vendors worldwide — including across the European data landscape
• Define data requirements in close collaboration with AI research and engineering teams
• Assess data quality, coverage, licensing, and compliance — ensuring all acquisitions meet ethical and legal standards, with strong emphasis on GDPR and EU data governance frameworks
• Build and manage a pipeline of data sources across multiple formats, languages, and domains
• Monitor market trends and emerging data sources to stay ahead of evolving AI training needs
• Establish and maintain quality control processes for incoming datasets
• Track acquisition metrics, budgets, and timelines — reporting on progress and ROI
• Coordinate with cross-functional teams including legal, engineering, and product to ensure seamless data integration
• Document sourcing strategies, vendor relationships, and acquisition workflows

About the Role

What if your ability to find, evaluate, and secure the right data could directly determine how intelligent the next generation of AI becomes? We're looking for a Data Acquisition Director to lead the strategy and execution of sourcing high-quality datasets that fuel cutting-edge AI systems — from text and language corpora to structured records, multimedia assets, and beyond. AI is only as good as the data it learns from. In this role, you'll be the person making sure that data is world-class — diverse, representative, ethically sourced, and precisely what our models need to get smarter. This is a strategic leadership role with real autonomy and direct impact on AI development at scale. This is a fully remote, flexible contract role. No prior AI experience is strictly required — but you do need a proven track record in data sourcing, vendor management, partnerships, or content acquisition.

• Organization: Alignerr
• Type: Hourly Contract
• Location: Remote
• Commitment: 20–40 hours/week

Who You Are

• Experienced in data sourcing, content acquisition, licensing, vendor management, or a related strategic function
• Strong negotiator with a track record of building productive partnerships and closing deals
• Analytical and detail-oriented — you can evaluate data quality and fitness-for-purpose with a critical eye
• Comfortable working across diverse data types: text, audio, images, structured records, and more
• Excellent communicator who can translate technical data needs into clear sourcing requirements
• Self-directed and organized — you thrive with autonomy and manage competing priorities with ease
• Familiar with data privacy, licensing frameworks, and ethical considerations in data collection — GDPR expertise is highly valued
• Intellectually curious about AI and motivated by the opportunity to shape how intelligent systems learn

Nice to Have

• Background in data science, information management, digital media, publishing, or research
• Experience sourcing data specifically for machine learning or AI training pipelines
• Familiarity with data annotation, labeling, or crowdsourcing workflows
• Deep knowledge of GDPR, the EU AI Act, and international data regulations
• Experience managing distributed or remote teams and vendor networks across Europe
• Multilingual skills — German and English required; additional European languages a strong plus
• Prior work with research institutions, archives, or large-scale content repositories

Why Join Us

• Work on cutting-edge AI projects alongside world-leading research labs
• Fully remote and flexible — work when and where it suits you
• High-autonomy leadership role with strategic influence over AI development
• Shape the foundation that AI systems are built on — your work has outsized impact
• Collaborate with a global, interdisciplinary team of researchers, engineers, and specialists
• Potential for ongoing work and contract extension as new projects and data needs emerge