As a member of our operations team, you will be accountable for driving revenue by ensuring that Scale AI meets customer commitments in a timely manner while maintaining the highest quality standards. You will manage workstreams in the field of Quality Control by building and running solutions, tools, and processes, and while working with a cross-functional team including Customer Operations, Product, Engineering, and many others.
This role sits at the core of our Quality Control (QC) function. You will build and scale quality systems from the ground up, including documentation, audit frameworks, rejection rubrics, performance tracking, and feedback loops.
You will solve ambiguous quality challenges in a fast-moving robotics environment, identifying root causes, reducing error rates, and driving operational excellence. Over time, you will take increasing ownership of quality strategy, efficiency optimization, and customer-facing quality initiatives.
The ideal candidate is analytical, structured, detail-oriented, and highly ownership-driven. You care deeply about building scalable systems that prevent errors before they happen and create clarity for both internal teams and contributors.
You will:
- Build and scale core Quality Control (QC) processes and frameworks
- Design and maintain clear quality guidelines, rejection rubrics, and project rules
- Track and improve quality performance (audits, rejection rates, false negatives, common errors)
- Own day-to-day quality delivery against customer standards
- Identify root causes of quality misses and implement corrective actions
- Build structured feedback loops for reviewers
- Develop and maintain quality performance trackers and reporting
- Partner cross-functionally to resolve quality bottlenecks
- Optimize QC efficiency (touches per task, AHT, cost per hour, team balance)
- Support QC team planning and resource allocation
Ideally, you'd have:
- Excellent communication skills in English and Spanish
- +2 years of experience in operations, quality control, or process improvement roles
- Strong analytical skills and comfort working with performance metrics
- Experience building structured documentation and operational frameworks
- Ability to balance quality standards with operational efficiency
- Experience working in data-heavy or performance-driven environments
- Familiarity with SQL or strong analytical capabilities
- Empathy for contributors performing physical data collection tasks
