About the Role

Labelbox’s mission is to build the best products for humans to advance artificial intelligence. As a Workforce Project Manager, you will work across engineering, customer, and data labeling teams to create highly accurate datasets. This is a unique, cross-functional position where you will be the go-to person for successful project outcomes for customers.

Your Day to Day

• Create a partner success model with partner QBRs, feature roadmap alignment and growth strategy with workforce partners.

• Create an operating model that is adopted repeatedly across a highly scaled number of workforce partners.

• Work cross-functionally with Product Management, Sales, and leadership to align and identity new workforce partnership opportunities.

• Help customers build production-grade data labeling pipelines.

• Track and analyze metrics to deliver remarkable customer service. Accuracy, precision, time-to-delivery, speed, and cost are the key metrics for a successful project.

• Lead large-scale data operations projects between customers and workforce teams.

• Assess and manage data labeling workforce performance to help them deliver the best results.

• Continuously improve quality and throughput of our data labeling services.

• Develop policies, guidelines, and workflows pertaining to data management and labeling services.

• Set up processes for data driven decision making for BPO matchmaking, BPO quality rating, and BPO customer rating.

About You

• Experience with establishing scalable and repeatable operating models with BPOs.

• Proactively find ways to improve and scale up workforce efforts.

• A passion for data and quality.

• Strong analysis and troubleshooting skills.

• An ability to navigate and advise on efforts related to complex customer requests or projects, gathering additional human resources for assistance if needed.

• A strong motivation to work closely with customers to create the best possible experiences with Labelbox.

• Assertive, positive, and effective communication skills in English – both written and verbal – with considerable attention to detail and the ability to present and influence.

• Demonstrated problem-solving ability, particularly in complex technical situations.

• Relevant professional experience in data labeling for ML.

• Experience building and/or QAing datasets.

• At least 5 years of experience with analytical software such as Excel.

• Vendor management experience.

Nice to Have

• Experience working with Language or Labeling/Linguistics.

• Experience working on computer vision use cases.

• Experience working as a Quality Assurance Analyst (QAA).

• Experience scoping and developing ontologies and taxonomies.