Portuguese (Brazil) 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

Free transport and bike-to-work perks

Job summary

Welo Data is seeking Data Labeling Associates in California to evaluate AI outputs and ensure cultural context and safety in Arabic datasets. This role requires professional-level proficiency in Portuguese (Brazil), a bachelor's degree, and at least 2 years of experience in AI safety. Responsibilities include critiquing Arabic AI outputs and refining guidelines based on real-world contexts. Benefits include gourmet dining, modern collaborative spaces, and comprehensive medical coverage.

Qualifications

• 2+ years of experience in GenAI safety focusing on identifying bias and risks.
• 1–2 years of experience in professional writing, journalism, or content creation.
• Ability to make sound judgment calls in ambiguous scenarios.

Responsibilities

• Critique Arabic AI outputs for accuracy, fluency, and tone.
• Identify bias, risks, and failure modes in Arabic datasets.
• Refine evaluation frameworks to reflect real-world Arabic dialects.

Skills

Professional-level proficiency in Portuguese (Brazil)

B2 level or superior English skills

Professional writing experience

Safety & Trust in Generative AI

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 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

• 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.