Portuguese (Brazil) Data Labeling Associate - WA based

Welo Data; Redmond (WA); On-site; USD 38,641 - 55,035; Full time

Benefits offered by this job

Gourmet Dining

Snack Suites

Commuter Support

Comprehensive Medical, Dental, and Vision Insurance

401(k) and HSA eligibility

Job summary

Welo Data in Redmond is looking for Data Labeling Associates for Project Perseus. This innovative role entails evaluating AI systems' handling of Arabic nuances, focusing on accuracy, safety, and cultural context. Candidates must possess professional-level Portuguese and a relevant degree, along with 2+ years of experience in GenAI safety. Premium benefits include gourmet dining, commuter support, and comprehensive medical plans, making this a unique opportunity for those passionate about AI development.

Qualifications

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

Responsibilities

• Critique Arabic AI outputs for accuracy and fluency.
• Identify bias and risks in Arabic datasets.
• Refine evaluation frameworks for real-world dialects.

Skills

Professional-level proficiency in Portuguese (Brazil)

B2 level English proficiency

Professional writing experience

AI safety expertise

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 Portuguese (Brazil) 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: California (On-Site: San Francisco, Sunnyvale, or Burlingame)
• Pay Rate: 34 $ (per hour)

What We’re Looking For:

• Linguistic Mastery: Professional-level proficiency in Portuguese (Brazil) 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:

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.