Italian 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

Commuter support perks

Job summary

Welo Data is seeking Data Labeling Associates for Project Perseus in San Francisco, California. This fast-paced role involves evaluating AI systems for their handling of Italian language nuances and safety concerns. Candidates should possess professional-level Italian proficiency, a bachelor's degree, and 2+ years of experience in AI safety. Benefits include gourmet meals, modern amenities, and comprehensive medical coverage. This position is full-time and offers significant opportunities for growth in AI evaluation.

Qualifications

• Professional-level proficiency in Italian is required.
• Bachelor's degree or higher needed.
• 2+ years of AI safety expertise focused on Generative AI.

Responsibilities

• Critique Italian AI outputs for accuracy and fluency.
• Identify bias and risks in Italian datasets.
• Refine evaluation frameworks to reflect real-world Italian contexts.

Skills

Professional-level proficiency in Italian

B2 level or superior English skills

1–2 years of professional writing experience

2+ years of AI safety expertise

Critical thinking

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.

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 Italian language nuances, cultural context, and safety boundaries.

The Mission: Human-in-the-Loop Excellence

• Model Evaluation: Critique Italian 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 Italian datasets.
• Guideline Evolution: Apply complex linguistic guidelines thoughtfully and help refine evaluation frameworks to reflect real‑world Italian 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 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.