German Data Labeling Associate - NYC based

Welo Data; New York (NY); Vor Ort; USD 38.641 - 55.035; Vollzeit

Benefits dieser Stelle

Free breakfast, lunch, and dinner

Snack suites with premium coffee

Modern collaborative spaces

Comprehensive Medical, Dental, and Vision

401(k) and HSA eligibility

Commuter support

Zusammenfassung

Welo Data is seeking Data Labeling Associates for Project Perseus in New York City. This role is focused on enhancing generative AI systems through evaluation of German outputs and addressing AI safety challenges. Candidates should possess native-level German proficiency and relevant experience in AI safety, along with strong writing and critical thinking skills. The position offers gourmet dining benefits, modern workspaces, and comprehensive medical packages. This is a unique opportunity to significantly contribute to AI system evaluation and improvement.

Qualifikationen

• 2+ years of experience in GenAI safety.
• 1–2 years of experience in professional writing, journalism, or content creation.

Aufgaben

• Critique German AI outputs for accuracy, fluency, and tone.
• Identify bias, risks, and failure modes in Arabic datasets.
• Apply complex linguistic guidelines thoughtfully.
• Identify trends in model performance and communicate findings.
• Participate in team syncs to ensure quality across AI workstreams.

Kenntnisse

Native-level German proficiency

B2 level English skills

Professional writing experience

AI safety expertise

Critical thinking

Technical agility

Ausbildung

University Degree (Bachelor's or higher)

Jobbeschreibung

Refine the Future of Multilingual AI

Are you a native German speaker with a professional background in writing and a keen eye for AI safety?

Welo Data is looking for Data Labeling Associates for Project Perseus.

This is not a traditional annotation role. You will be working at the intersection of human judgment and machine learning, evaluating how cutting-edge AI systems handle Arabic language nuances, cultural context, and safety boundaries.

The Mission: Human-in-the-Loop Excellence

• Model Evaluation: Critique German AI outputs for accuracy, fluency, and tone, providing structured feedback to drive model improvement.
• Safety Engineering: Use your 2+ years of GenAI safety experience to identify bias, risks, and failure modes in Arabic datasets.
• Guideline Evolution: Apply complex linguistic guidelines thoughtfully and help refine evaluation frameworks to reflect real-world German dialects and contexts.
• Strategic Insights: Identify trends in model performance and communicate findings clearly to technical stakeholders.
• Collaborative Calibration: Participate in team syncs to ensure consistent quality across global AI workstreams.

Project Details

• Employment Type: W2 Full-Time Employee
• Hours: 40 hours/week
• Location: New York City
• Pay Rate: 34 $ (per hour)

What We’re Looking For

• Linguistic Mastery: Native-level German proficiency and a University Degree (Bachelor’s or higher).
• English Proficiency: B2 level or superior English skills to navigate technical guidelines and stakeholder syncs.
• Professional Writing: 1–2 years of experience in professional writing, journalism, or content creation.
• AI Safety Expertise: 2+ years of experience focusing on Safety & Trust in Generative AI data delivery.
• Critical Thinking: The ability to make sound judgment calls in ambiguous "grey area" scenarios.
• Technical Agility: A natural curiosity about LLMs and the confidence to flag issues when a model's behavior feels "off".

Premium Campus Benefits

Joining Project Perseus on-site gives you access to a world-class work environment:

• Gourmet Dining: Free breakfast, lunch, and dinner with a wide variety of cuisines.
• Snack Suites: Micro-kitchens stocked with premium coffee, beverages, and healthy treats.
• Campus Features: Modern collaborative spaces and unique amenities like rooftop nature parks (at select locations).
• Full Security: Comprehensive Medical, Dental, and Vision + 401(k) and HSA eligibility.
• Commuter Support: Free transport, shuttles, and bike-to-work perks.

Why This Role

This is an opportunity to move beyond traditional data work and play a direct role in how AI systems are evaluated and improved. The work is fast-moving, collaborative, and increasingly central to how modern AI systems are built and deployed.