German Marketing Documents Specialist

About OpenTrain

OpenTrain is the #1 platform for building careers in AI training and data labeling. We help people discover projects, track work across platforms, and build a unified AI-training portfolio that grows into a durable freelance career.

We connect experienced contributors with projects that directly influence how AI systems behave and learn, while making it simple to apply, work, and get paid on flexible schedules.

Why AI training matters

AI training (also called data labeling or annotation) is the human side of building intelligent systems: people create, review, and rate real-world examples that models learn from. Contributors shape model outputs across language, search, vision, and beyond.

This role puts your professional marketing and documentation skills to work improving the quality of German-language training data used to teach next-generation AI systems.

The role

You will create, review, and refine German-language marketing documents so they reflect authentic business scenarios and high-quality marketing practice. Your work will be used as training data and evaluation material to improve model understanding of marketing language and documents.

This is a remote, part-time contractor role with a minimum commitment of 20+ hours per week, ideally filled by someone based in the US with native-level German proficiency.

• Employment type: Contractor, Part-time
• Time requirement: 20+ hours/week
• Location: Remote (ideally US-based)
• Language requirement: Native-level German (written and spoken)

What you’ll do

Daily tasks center on creating and evaluating marketing collateral in German, ensuring authenticity, clarity, and alignment with real-world marketing strategies. You’ll collaborate with a global AI training team and provide precise feedback used for model development and quality assurance.

• Create, review, and refine brochures, presentations, reports, and other marketing documents in German
• Evaluate materials for accuracy, coherence, tone, and relevance to business contexts
• Rate and annotate documents as part of evaluation/data-collection tasks for model training
• Provide actionable feedback and documentation that reflects Fortune 500 marketing standards
• Maintain confidentiality and uphold data integrity for all deliverables

Requirements

We need candidates who can combine marketing domain expertise with precise language skills. All required qualifications come from the role description and must be met.

• Native-level proficiency in German, both written and spoken
• Minimum 3 years of experience in marketing documentation, preferably for Fortune 500 companies
• Bachelor’s degree or higher in Marketing, Communications, Business, or related field
• Strong command of Microsoft Word, Excel, and PowerPoint
• Exceptional attention to detail and commitment to accuracy
• Proven ability to manage multiple projects and work independently in a fast-paced remote environment

Helpful background (preferred)

These are not required but will make you particularly competitive for the role and for work on related AI training projects.

• Experience living or working in the US while using native-level German
• Direct experience with AI training, data annotation, or technology-driven marketing work
• Familiarity with digital marketing trends and document automation tools

Pay, labeling details, and how it works

Compensation is hourly, paid per time worked. The listed range for this project is $10–$55 per hour with rates up to $55/hr. Tasks include evaluation/rating and data-collection of document inputs and use a custom labeling tool (listed as OTHER).

To apply, create or sign in to your OpenTrain account, complete any required qualification tasks, and submit your application. Contributors are selected based on language ability, marketing documentation experience, and quality on qualification tasks.

• Pay type: Hourly (pay-per-hour)
• Rate: $10–$55 per hour (up to $55/hr)
• Data type: Documents — label types include evaluation/rating and data collection
• (project-specific tool)