Project Perseus | Data Labeling Associate - Arabic Speakers (Human-in-the-Loop AI)

Data Labeling Associate

Welo Data is looking for sharp, curious, and detail-oriented individuals to join our team as Data Labeling Associate. This is not a traditional annotation role. You'll be working directly with cutting-edge AI systems — evaluating outputs, identifying gaps, and helping improve how these systems behave in real-world scenarios. The work sits at the intersection of data quality, model evaluation, and human judgment, where your ability to think critically matters just as much as following guidelines.

We're looking for people who are naturally curious about AI, comfortable forming opinions, and confident in contributing to conversations with teammates, leads, and stakeholders.

Project Details

• Job Title: Data Labeling Associate
• Hiring in: NYC, Seattle, Bellevue, Redmond, San Francisco, Sunnyvale, Burlingame, Austin, Los Angeles, Washington DC, Chicago, Boston
• Hours: Full-time, 40 hours per week
• Employment Type: W2 Full-Time Employee
• Work Authorization: Must be authorized to work in the U.S. (no visa sponsorship)
• Pay Rate: $34/hour
• Contract Duration: 1-year contract with possibility of extension

Important: This is a 100% onsite position — remote work is not available for this role. To be considered, candidates must be located in or able to commute to one of the following cities: New York City, Seattle, Bellevue, Redmond, San Francisco, Sunnyvale, Burlingame, Austin, Los Angeles, Washington DC, Chicago, Boston. Please only apply if you meet this location requirement.

What You'll Do

• Evaluate AI model outputs and provide structured, high-quality feedback
• Perform audit-based reviews of data and model behavior — identifying patterns, edge cases, and failure modes
• Apply guidelines thoughtfully — and flag when they don't reflect real-world scenarios
• Contribute to improving evaluation frameworks, not just executing them
• Identify trends in model performance and communicate insights clearly
• Participate in team discussions, calibrations, and stakeholder syncs
• Partner with leads and cross-functional teams to refine quality standards
• Document findings in a clear, concise, and actionable way

What We're Looking For

• Native-level language proficiency and a university degree (Bachelor's or higher).
• B2 or superior level of English.
• 1–2 years of professional writing experience with strong, structured writing skills
• Ability to apply complex writing rules and guidelines consistently
• Strong understanding of safety considerations in GenAI data delivery, with 2+ years of relevant experience
• Strong critical thinking and attention to detail
• Ability to make sound judgment calls in ambiguous situations
• Naturally curious about AI, technology, and how systems behave
• Comfortable speaking up, asking questions, and contributing ideas
• Strong written and verbal communication skills
• Ability to stay consistent while working with evolving guidelines
• Experience in data quality, QA, annotation, or analysis is helpful — but not required

Benefits

• Paid Vacation: 6 days
• Paid Company Holidays: 2 days (Memorial Day and Labor Day)
• Paid Sick Leave: accrued per applicable state law and company policy
• Medical, Dental, and Vision Insurance (eligibility applies)
• Health Savings Account (HSA)
• 401(k) Retirement Plan
• Employee Assistance Program
• Additional voluntary benefits (life, accident, critical illness, etc.)
• Free Gourmet Food: Free breakfast, lunch, and dinner are provided, featuring a wide variety of cuisines in multiple cafes.
• Micro-kitchens & Snacks: Offices are stocked with free snacks and beverages, including premium coffee and La Croix.
• Unique Campus Features: Some locations include roof-top nature parks
• Commuter Benefits: Free transport, shuttles, and sometimes bike-to-work perks.

$34 - $34 an hour 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.