Product Quality Analyst

Note:

This role is fully remote but you must be in EST or CST time zone.

AI Foundation develops the core ML and AI systems that power personalized digital experiences across the platform. These systems rely on human judgment to ground their intelligence in the nuances of culture, personal taste, and real-world user habits.

We're looking for a Senior Product Quality Analyst / Annotation Operations Specialist to deliver high-quality human judgments that provide ground truth for evaluation, support model fine-tuning, and guide the alignment of LLM-based evaluators. You'll lead annotation projects, drive improvements in annotation quality, and establish scalable workflows across the AI Foundation team.

• Lead end-to-end execution of human annotation projects, from intake, scoping, and sourcing to delivery.
• Serve as the primary point of contact across data science, engineering, and partner teams to map annotation requirements to the most efficient internal or vendor pipelines.
• Maintain a roadmap of annotation needs, prioritizing requests and coordinating the appropriate internal or external annotation resources.
• Manage vendors and coordinate contracts, onboarding, and related reviews with legal, security, privacy, finance, and accounting.
• Develop and maintain reusable annotation frameworks and guidelines that can be adopted across teams, and consult on annotation task and rubric design.
• Run feedback sessions with modeling teams to identify model strengths, failure patterns, and evaluation gaps.
• Evaluate annotation quality, identify sources of disagreement, and work with teams and vendors to systematically improve guidelines and outputs.
• Chart best practices and operational documentation for a newly formalized function, partnering closely with dedicated data scientists.

• Background in data operations (Data Ops), annotation ops, model evaluation, product quality, or technical program management.
• Hands-on experience managing, coordinating, or designing data annotation workflows—this is an operational and program-level ownership role, not a direct labeling position.
• Demonstrated experience at a scaled tech company or working directly with established data annotation vendors.
• Familiarity with ML-driven products and human evaluation of AI/LLM-powered features.
• Proven ability to translate complex product and modeling needs into clear, scalable annotation guidelines and evaluation rubrics.
• Skilled at vendor onboarding, procurement coordination, and cross-functional project tracking.
• Exceptional cross-functional communication skills (a core deciding factor), with a demonstrated ability to navigate ambiguity, align technical teams, and coordinate operational stakeholders.
• A self-starter comfortable stepping into a 0-to-1 environment to formalize and streamline processes.

Direct/Indirect Management:
No

Top 3 Hard

Skills:

End-to-end data annotation workflow management, familiarity with AI/ML evaluation rubrics & guideline creation, vendor onboarding and procurement coordination.

Top 3

Soft Skills:

High-level cross-functional communication (critical stakeholder liaison), self-direction/navigating ambiguity in a new role, and rigorous project tracking across enterprise teams.

Target Profiles / Previous Titles:
Data Operations Manager, Annotation Ops Lead, Data Program Manager, Model Evaluation Specialist, Technical Product Quality Analyst. (Disqualifier: Pure data labelers without process/guideline ownership).

Nice-to-Have

Skills:

Experience interacting with AI collaboration tools (e.g., Claude, Codex), basic coding abilities, and experience scaling annotation pipelines from early-stage to operational maturity.

Strategic Impact & Influence:
The role delivers human judgments to ground…