Italian Data Labeling Associate - WA based

Welo Data; Redmond (WA); On-site; USD 63,000 - 77,000; Full time

Benefits offered by this job

Free breakfast, lunch, and dinner

Micro-kitchens with premium coffee

Modern collaborative spaces

Comprehensive Medical, Dental, and Vision

Free transport and bike-to-work perks

Job summary

Welo Data is hiring Data Labeling Associates in Redmond, Washington, to refine AI evaluation processes. Candidates must possess professional-level Italian proficiency and AI safety experience. Responsibilities include critique of Arabic AI outputs and applying linguistic guidelines. This role offers full-time employment with benefits like gourmet dining and commuter support. If you seek a fast-paced, collaborative environment in AI development, we want to hear from you.

Qualifications

• Professional-level proficiency in Italian is required for accurate model evaluation.
• B2 level or superior English skills needed for technical communication.
• 1-2 years of experience in professional writing, journalism, or content creation.
• 2+ years of experience focusing on Safety & Trust in Generative AI.
• Ability to make judgment calls in ambiguous scenarios.
• Curiosity about LLMs and ability to flag issues in AI models.

Responsibilities

• Critique Arabic AI outputs for accuracy and fluency.
• Identify bias and risks in Arabic datasets using safety engineering skills.
• Apply complex linguistic guidelines in model evaluation.
• Communicate model performance trends to technical stakeholders.
• Ensure consistent quality across global AI workstreams.

Skills

Professional-level proficiency in Italian

B2 or superior English skills

1–2 years of experience in professional writing

2+ years of experience in AI safety

Critical thinking

Technical agility regarding LLMs

Education

Bachelor's degree or higher

Job description

Refine the Future of Multilingual AI

Do you have professional-level proficiency in Italian and a background in writing, with attention to AI safety? Welo Data is looking for Data Labeling Associates for Project Perseus.

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: Washington State (On-Site: Redmond, Seattle, or Bellevue)
• Pay Rate: 34 $ per hour

What We’re Looking For

• Linguistic Mastery: Professional-level proficiency in Italian and a bachelor’s degree 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.