AI Operations Lead (Human-in-the-Loop) - NYC-based
Welo Data · New York, NY · 2 mo ago
On-siteManufacturingContract
The Mission: Quality Leadership at Scale
- Team Architecture: Lead and mentor a specialized team of Data Quality Analysts, fostering growth and managing high-performance output.
- Quality Ownership: Own the end-to-end quality loop, including audits, calibrations, and the identification of model performance trends.
- Strategic Translation: Turn ambiguous, evolving AI guidelines into structured direction for your teams.
- Stakeholder Partnership: Act as the primary representative for your team, aligning with global stakeholders on quality standards and program goals.
- Operational Innovation: Drive continuous improvement across tooling, evaluation methods, and hiring for specialized linguistic talent.
Project Details
- Job Title: AI Operations Lead
- Employment Type: W2 Full-Time Employee
- Hours: 40 hrs/week
- Location: New York City
- Pay Rate: $38/hour
Premium Perks & Benefits
- Gourmet Dining: Free breakfast, lunch, and dinner with a wide variety of cuisines.
- Wellness & Insurance: Comprehensive Medical, Dental, and Vision coverage + 401(k) and HSA.
- Time Off: 15 days of combined Paid Sick/Holiday time + Memorial Day and Labor Day.
- Campus Culture: Access to micro-kitchens, premium coffee, and unique features like rooftop nature parks.
- Commuter Support: Free shuttles, transport benefits, and bike-to-work perks.
Who We’re Looking For
- Education & Language: University degree (Bachelor’s or higher) and Native-level English proficiency are required.
- The Multilingual Edge: Proficiency in languages other than English is highly preferred, with a particular interest in candidates demonstrating bilingual mastery in French, Italian, German, Spanish, or Brazilian Portuguese.
- Industry Veteran: 5–8 years of experience in Data Quality, QA, or AI/ML operations.
- Proven Leader: 2+ years of experience managing teams in a high-scale data or AI environment.
- Strategic Mindset: Ability to "zoom out" to see patterns while maintaining deep attention to detail.
- Operational Agility: Comfortable navigating ambiguity and balancing speed with rigorous quality standards.
- Technical Interest: A genuine curiosity about how human feedback shapes the behavior of Large Language Models (LLMs).