AI Operations Lead (Human-in-the-Loop) - NYC-based

Welo Data; New York (NY); On-site; USD 79,000 - 104,000; Full time

Benefits offered by this job

Free breakfast, lunch, and dinner

Comprehensive Medical, Dental, and Vision coverage

15 days of Paid Sick/Holiday time

Access to micro‑kitchens and premium coffee

Free shuttles and transport benefits

Job summary

A technology-focused company in New York City is seeking a Data Quality Lead to guide high-impact teams dedicated to AI model evaluation. This role entails overseeing data quality operations, mentoring Data Quality Analysts, and ensuring high-performance standards. With a strong focus on leadership, the ideal candidate should have 5-8 years' experience in Data Quality and 2+ years in a management role. The position includes premium perks such as gourmet dining and comprehensive medical coverage.

Qualifications

• 5–8 years of experience in Data Quality, QA, or AI/ML operations.
• 2+ years of experience managing teams in a high‑scale data or AI environment.
• Native‑level English proficiency required.

Responsibilities

• Lead and mentor a team of Data Quality Analysts.
• Own the end‑to‑end quality loop, including audits and calibrations.
• Act as the primary representative for your team with stakeholders.

Skills

Leadership

Data Quality Management

Attention to Detail

Multilingual Proficiency

Operational Agility

Education

University degree (Bachelor’s or higher)

Job description

Lead the Teams Shaping the Future of AI – On‑Site [NYC]

Are you a strategic leader who thrives at the intersection of data quality and people operations? Welo Data is seeking a Data Quality Lead to oversee high‑impact teams of analysts dedicated to AI model evaluation.

This isn’t just a management role—it’s an opportunity to define how quality is measured in a human‑in‑the‑loop environment. You will act as the bridge between technical stakeholders and analyst teams, translating complex AI guidelines into clear, actionable operational excellence.

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

This role offers more than just a paycheck—it includes a world‑class workspace experience:

• 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.
• 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).