Global Head of Partnerships
•Easygenerator· 2h
SalesFull-timeMiddle East
2h ago
Pearltalent·8 days ago
Technical / Data Infrastructure
Remote
Full-time
Standard business hours with required overlap with US Pacific Time (PST)
Pearl works with the top 1% of candidates from around the world and connects them with the best startups in the US and EU. Our clients have raised over $5B in aggregate and are backed by companies like OpenAI, a16z, and Founders Fund. They’re looking for the sharpest, hungriest candidates who they can consistently promote and work with over many years. Candidates we’ve hired have been flown out to the US and EU to work with their clients, and even promoted to roles that match folks onshore in the US.
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At Pearl, we’re not just another recruiting firm—we connect you with exceptional opportunities to work alongside visionary US and EU founders. Our focus is on placing you in roles where you can grow, be challenged, and build long-term, meaningful careers.
Our client is a technology-driven company operating at the intersection of data, infrastructure, and machine learning. They build large-scale datasets that power advanced analytics and AI systems, helping organizations make better decisions using real-world visual and geospatial information. The company operates in a fast-paced, high-ownership environment where data quality and execution excellence are critical to customer success.
The Infrastructure Analyst (Data Creation Owner) is responsible for end-to-end ownership of a complex, judgment-driven data creation pipeline built from roadway video and imagery. This role ensures that infrastructure features such as roadway assets, signage, and surface conditions are accurately identified, classified, and delivered to customers at scale.
You will define standards, resolve ambiguous edge cases, and act as the final quality authority for datasets. This is a highly accountable role that works cross-functionally with Machine Learning and Customer Success teams while leading operational annotation teams. The ideal candidate is decisive, detail-oriented, and thrives in environments where speed, accuracy, and ownership must be carefully balanced.
You will ensure the delivery of high-quality, customer-ready datasets that directly support machine learning performance and customer outcomes. Your work will reduce ambiguity, improve data consistency, and increase delivery reliability across large-scale infrastructure datasets. You will help scale data operations while maintaining strict quality standards, enabling faster iteration and stronger customer satisfaction. Your ownership will directly influence operational efficiency, data accuracy, and long-term scalability.
End-to-End Data Ownership – 35%
Quality & Standards – 25%
Team Leadership – 20%
Cross-Functional Collaboration – 10%
Process Improvement & Scale – 10%