Arabic AI Safety & Data Evaluation Specialist

Welo Data; New York (NY); On-site; USD 63,000 - 77,000; Full time

Benefits offered by this job

Free breakfast, lunch, and dinner

Premium coffee and snacks

Comprehensive Medical, Dental, and Vision

401(k) and HSA eligibility

Free transport and bike-to-work perks

Job summary

Welo Data is hiring Data Labeling Associates in New York City for Project Perseus. The role involves evaluating Arabic language AI outputs and ensuring AI safety, requiring professional proficiency in Arabic and experience in writing and AI safety. You’ll critique models, identify biases, and collaborate with teams. Enjoy premium benefits like gourmet dining and comprehensive medical coverage. This position is not just about data; it’s about enhancing AI systems' performance and reliability.

Qualifications

• 2+ years of experience in GenAI safety.
• 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.
• Apply linguistic guidelines thoughtfully and refine evaluation frameworks.
• Identify trends in model performance and communicate findings.
• Participate in team syncs to ensure quality across AI workstreams.

Skills

Professional-level proficiency in Arabic

B2 level English skills

Professional writing experience

AI safety expertise

Critical thinking

Technical agility with LLMs

Education

Bachelor’s degree or higher

Job description

Welo Data is hiring Data Labeling Associates in New York City for Project Perseus. The role involves evaluating Arabic language AI outputs and ensuring AI safety, requiring professional proficiency in Arabic and experience in writing and AI safety. You’ll critique models, identify biases, and collaborate with teams. Enjoy premium benefits like gourmet dining and comprehensive medical coverage. This position is not just about data; it’s about enhancing AI systems' performance and reliability.