German Data Labeling Associate - California based

Welo Data; San Francisco (CA); On-site; USD 38,641 - 55,035; Full time

Benefits offered by this job

Free breakfast, lunch, and dinner

Micro-kitchens with premium snacks

Modern collaborative spaces

Comprehensive Medical, Dental, and Vision

401(k) and HSA eligibility

Commuter support perks

Job summary

Welo Data is seeking native German speakers for the role of Data Labeling Associates in San Francisco. This position involves evaluating AI systems' handling of Arabic language nuances, with responsibilities including model evaluation and bias identification. Ideal candidates will hold a university degree, have experience in professional writing, and be proficient in both German and English. We offer full-time positions with gourmet dining, modern campus features, and comprehensive medical benefits.

Qualifications

• 2+ years of experience focusing on Safety & Trust in Generative AI.
• 1–2 years of experience in professional writing, journalism, or content creation.
• Ability to critique AI outputs for accuracy and tone.

Responsibilities

• Critique Arabic AI outputs for accuracy, fluency, and tone.
• Identify bias and risks in Arabic datasets.
• Apply complex linguistic guidelines in evaluations.
• Communicate trends in model performance to stakeholders.
• Participate in team syncs to maintain quality across projects.

Skills

Native-level German proficiency

B2 level English proficiency

Professional writing experience

AI safety expertise

Critical thinking

Technical agility

Education

University Degree (Bachelor’s or higher)

Job description

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 Arabic 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 Arabic 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: California (On‑Site: San Francisco, Sunnyvale, or Burlingame)
• 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

• 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.