Project Perseus | Data Quality Team Lead (Human-in-the-Loop AI)

Data Quality Lead

Welocalize is looking for a Data Quality Lead to oversee teams of Data Quality Analysts supporting AI model evaluation and improvement.

This role is equal parts people leadership, quality ownership, and operational thinking.

You'll be responsible for guiding teams through fast-changing work, ensuring high-quality output, and acting as a bridge between analysts and stakeholders. This is not just about managing throughput it's about shaping how quality is defined, measured, and improved in a human-in-the-loop environment.

Important: This is a 100% onsite position remote work is not available for this role. To be considered, candidates must be located in or able to commute to one of the following cities: NYC, Seattle, Bellevue, Redmond, San Francisco, Sunnyvale, Burlingame, Austin, Los Angeles, Washington DC, Chicago, Boston. Please only apply if you meet this location requirement.

What You'll Do

• Lead and support a team of Data Quality Analysts
• Oversee overall operational performance across workflows and teams
• Ensure team activities align with broader business objectives and program goals
• Drive the success of key initiatives across quality, delivery, and team performance
• Own quality across workflows including audits, calibrations, and feedback loops
• Identify trends, risks, and gaps in model performance and data quality
• Translate ambiguous or evolving guidelines into clear team direction
• Run calibrations and ensure consistency across reviewers
• Partner with stakeholders to align on quality standards and expectations
• Prioritize and support hiring of linguists and specialized talent as needed
• Drive continuous improvement across processes, tooling, and evaluation methods
• Step into edge cases and complex decisions when needed
• Support team growth, coaching, and performance management

What We're Looking For

• 58 years of experience in data quality, QA, AI/ML operations, or related fields
• 2+ years of experience leading teams in data quality, QA, or AI/ML-related work at scale
• Native-level English proficiency and a university degree (Bachelor's or higher)
• Proficiency in languages other than English is preferred, with particular interest in candidates demonstrating bilingual mastery in French, Italian, German, Spanish, or Brazilian Portuguese.
• Strong operational mindset with experience managing performance across multiple workstreams
• Proven ability to drive quality, delivery, and process improvements
• Strong judgment and ability to operate in ambiguity
• Comfortable interacting with stakeholders and representing the team
• Ability to balance quality, speed, and evolving priorities
• Strong communication and organizational skills
• Deep attention to detail, with the ability to zoom out and see patterns
• Interest in AI and how human feedback shapes model behavior

This leader is accountable for end-to-end operational success including resource management, process optimization, and continuous improvement.

You'll be expected to think beyond day-to-day execution and focus on long-term outcomes, ensuring the team consistently meets targets across quality, delivery, and overall program performance.

Benefits

• Paid Vacation: 6 days
• Paid Company Holidays: 2 days (Memorial Day and Labor Day)
• Paid Sick Leave: accrued per applicable state law and company policy
• Medical, Dental, and Vision Insurance (eligibility applies)
• Health Savings Account (HSA)
• 401(k) Retirement Plan
• Employee Assistance Program
• Additional voluntary benefits (life, accident, critical illness, etc.)
• Free Gourmet Food: Free breakfast, lunch, and dinner are provided, featuring a wide variety of cuisines in multiple cafes.
• Micro-kitchens & Snacks: Offices are stocked with free snacks and beverages, including premium coffee and La Croix.
• Unique Campus Features: Some locations include roof-top nature parks
• Commuter Benefits: Free transport, shuttles, and sometimes bike-to-work perks.

$43.50 - $43.50 an hour Why This Role You'll be at the center of how AI systems are evaluated in the real world helping define quality, guide teams, and influence how models improve over time.