Spanish Data Labeling Associate - NYC based

Welo Data; New York (NY); On-site; USD 68,000 - 72,000; 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

Commuter support and bike-to-work perks

Job summary

Welo Data is seeking Data Labeling Associates in New York City. The role involves evaluating AI systems handling Arabic language nuances and requires professional-level Spanish proficiency, a bachelor’s degree, and AI safety expertise. Candidates should possess strong professional writing skills and critical thinking abilities. With benefits including gourmet dining and comprehensive medical coverage, this position represents a move beyond traditional data work, emphasizing collaboration in AI model evaluation and improvement.

Qualifications

• Professional-level proficiency in Spanish.
• B2 level or superior English skills for technical guidelines.
• 1–2 years of experience in professional writing or journalism.
• 2+ years focusing on Safety & Trust in Generative AI.

Responsibilities

• Critique Arabic AI outputs for accuracy and fluency.
• Identify bias and risks in Arabic datasets.
• Apply linguistic guidelines for evaluation.
• Communicate findings to technical stakeholders.
• Participate in team syncs for quality assurance.

Skills

Linguistic Mastery

Professional Writing

Critical Thinking

Technical Agility

Education

Bachelor's degree or higher

Job description

Refine the Future of Multilingual AI

Do you have professional-level proficiency in Spanish and a background in writing, with attention to 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: New York City (On‑Site)
• Pay Rate: 34 $ (per hour)

What We’re Looking For

• Linguistic Mastery: Professional-level proficiency in Spanish 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 judgement 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.