Quality Project Associate

About Abaka AI Abaka AI is built on one mission: to be the world’s most trusted data partner for AI companies. More than 1,000 industry leaders across Generative AI, Embodied AI, and Automotive AI rely on us to power their data pipelines. With our headquarters in Silicon Valley—and teams in Paris, Singapore, and Tokyo—we support global partners with fast, reliable, and scalable data solutions. Our offerings include a diverse catalog of off-the-shelf datasets (image, video, multimodal, reasoning, 3D, and beyond) as well as comprehensive data collection and annotation services. Whether teams need raw data, curated datasets, or full-cycle data engineering, Abaka AI provides the foundation for building high-performance AI systems. About the Role As a Quality Project Associate at Abaka AI, you will help build and scale the quality systems that power our global AI data operations. This is a highly cross-functional role focused on improving data quality, reviewer alignment, fraud prevention, and operational compliance across large-scale AI data annotation programs. You will work closely with Project Managers, Operations teams, Reviewers, and Leadership to identify quality risks, investigate root causes, and develop scalable solutions that improve project outcomes. Rather than simply auditing completed work, you will help design the systems, processes, and governance frameworks that drive quality at scale. This is a high-impact role at the intersection of quality assurance, crowdsourcing operations, trust & safety, and project management. Responsibilities Build and improve quality assurance and compliance systems across AI data annotation projects Design quality standards, review processes, escalation workflows, and operational governance frameworks Develop quality metrics, auditing methodologies, reviewer calibration programs, and random inspection systems Monitor quality risks across large-scale annotator and reviewer pipelines Identify and mitigate fraud, abuse, and quality risks, including multi-accounting, VPN/proxy usage, AI-generated responses, and low-quality contributors Investigate root causes behind quality issues such as declining acceptance rates, reviewer misalignment, annotation quality degradation, workflow inefficiencies, and client requirement mismatches Develop corrective actions and scalable solutions that improve project quality and customer acceptance rates Improve reviewer consistency, accountability, and operational traceability across projects Collaborate cross-functionally with Project Managers, Operations, Product, QA teams, and Leadership to drive quality initiatives Support the development of scalable systems and processes that improve quality outcomes without increasing operational overhead Contribute to 0→1 initiatives that strengthen quality management and operational excellence across the organization Qualifications Strong operational foundation in quality assurance, crowdsourcing operations, trust & safety, compliance operations, project operations, or related fields Experience identifying and solving operational problems through process design, governance frameworks, or quality systems Strong analytical thinking and root cause analysis capabilities Understanding of crowdsourcing challenges such as reviewer inconsistency, contributor quality management, fraud prevention, and operational scalability Ability to design scalable, traceable, and repeatable operational processes High ownership mindset with the ability to operate independently in ambiguous environments Strong written and verbal communication skills Excellent stakeholder management and cross-functional collaboration abilities Detail-oriented with a commitment to operational excellence Interest in AI, machine learning, and large-scale data operations Growth-oriented mindset with a bias toward continuous improvement and execution Preferred Qualifications Experience working at AI data platforms, crowdsourcing platforms, trust & safety organizations, or large-scale annotation operations Experience managing reviewers, contributors, quality programs, or operational teams Familiarity with quality dashboards, QA tooling, workflow management systems, or operational reporting platforms Experience improving acceptance rates, quality metrics, or operational performance at scale Startup or high-growth environment experience Experience building quality systems and governance frameworks from 0→1 Familiarity with AI, LLM, data annotation, or human-in-the-loop workflows Compensation & Benefits The base salary range for this position is $70,000 - $120,000 USD annually. Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work at Abaka AI. This role is eligible for equity, as well as a comprehensive benefits package (health, dental, vision, PTO, flexible work schedule).