Quality Project Associate
Abaka AI
Quality Project Associate
Abaka AI
AI data lifecycle and annotation platform
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 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.
We're hiring a Quality Project Associate to help REX trainers and reviewers apply client quality standards consistently across AI data campaigns. You'll work with the Quality Lead and Project Managers to review annotations, evaluate screener responses, and give trainers specific feedback they can use on their next task.
You'll also help the team understand why errors recur. For example, if two reviewers score the same robotics annotation differently, you'll compare their reasoning with the rubric, identify the point of disagreement, and bring the example to the Quality Lead for clarification. Once the team agrees on an interpretation, you'll help turn it into guidance that other reviewers can use.
If you thrive in detail-driven, high-ownership environments and want to help build the quality foundation behind a fast-moving AI data company, this role offers immediate and lasting impact.
Review samples of trainer submissions against campaign rubrics and approved examples. Record each issue, its severity, and the evidence behind your assessment.
Give trainers clear, actionable feedback that identifies what needs to change and points them to the relevant guideline. Review corrected submissions to confirm the issue was resolved.
Support screener and pilot reviews by scoring sample tasks, checking scores against approved reference answers, and flagging ambiguous criteria before production begins.
Prepare examples for reviewer calibration sessions, compare how reviewers scored the same work, and document decisions so the team can apply them consistently.
Track pass rates, rework rates, and recurring errors in Airtable or spreadsheets. Summarize trends for project leads and distinguish isolated mistakes from issues affecting multiple trainers.
Escalate quality issues that could affect a delivery. Work with Training and Project Operations to update guidance, share examples, and check whether the same errors recur in later batches.
0 to 2 years of experience in quality assurance, data annotation, evaluation, research, project operations, or a related field. Recent graduates are welcome to apply, and relevant internships and academic projects count.
Strong attention to detail and analytical judgment. You can apply a rubric consistently, explain a score using evidence from the task, and recognize when the instructions leave room for interpretation.
Clear written communication and the ability to give constructive feedback to trainers and reviewers from diverse backgrounds.
Comfortable using spreadsheets to filter review results, calculate basic quality metrics, and identify patterns.
Able to manage review deadlines and adapt when client requirements change.
Familiarity with Airtable, Slack, or annotation platforms.
Experience with AI data evaluation.
Proficiency in an additional language.
The base salary range for this position is 70k - 120k 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).
Abaka AI helps companies build AI by handling data and infrastructure for large-scale AI systems. It offers end-to-end data processing across the AI data lifecycle, including data collection, cleaning, annotation, training support, and model evaluation for multimodal data. Its Abaka Forge Platform uses AI-driven pre-labeling and automation, plus a network of over one million annotators and multi-tier verification to ensure quality, and it also provides embedded data professionals to support client workflows. The company aims to deliver scalable, well-labeled training data for models like large language models and other AI systems, serving sectors such as automotive AI, generative AI, and embodied AI.
Explore more opportunities at Abaka AI