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

Welo Data; Washington; On-site; USD 79,000 - 85,000; Full time

Benefits offered by this job

Free gourmet dining

Comprehensive Medical, Dental, and Vision

15 days of combined Paid Sick/Holiday time

Access to micro-kitchens and rooftop parks

Commuter support with free shuttles

Job summary

A leading AI and Data firm is seeking a Data Quality Lead to oversee teams dedicated to AI model evaluation. This role requires strategic leadership, where you will manage high-impact teams of analysts and own the end-to-end quality loop. Ideal candidates have 5-8 years in Data Quality and a university degree. The position is on-site in Washington with a competitive pay rate of $38/hour and comprehensive benefits including gourmet dining and wellness 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

• Oversee teams of Data Quality Analysts for AI model evaluation.
• Own the end-to-end quality loop including audits and model performance trends.
• Translate complex AI guidelines into actionable operational excellence.

Skills

Team Leadership

Data Quality Management

Attention to Detail

Operational Agility

Multilingual Proficiency

Education

University degree (Bachelor’s or higher)

Job description

Lead the Teams Shaping the Future of AI – On-Site [WA]

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: Washington (On-site) — Redmond, Seattle, or Bellevue
• 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.
• 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).