Poolside was looking for a Member of Engineering (Human Data)

ABOUT THE ORGANIZATION In the coming decade, Artificial General Intelligence will emerge. Only a select few organizations will successfully achieve this milestone. Their capacity to accumulate strategic advantages will determine their ultimate success. These entities will operate with unprecedented speed, attracting exceptional global talent. They will pioneer advanced research, engineering, infrastructure, and large-scale deployment. Continuous model training and enhancement will be their hallmark. They will secure substantial financial backing, develop powerful economic mechanisms, and remain intensely committed to user and customer success. Our mission is to establish a technological ecosystem where AI drives economic productivity and scientific advancement. TEAM COMPOSITION We operate as a distributed team spanning Europe and North America, convening monthly for three-day in-person sessions and biannual extended collaborative retreats. Our research and production teams blend research-oriented and engineering-focused professionals, united by a deep commitment to system quality and robust software development principles. We believe superior engineering accelerates development cycles, enabling cumulative progress. ROLE DESCRIPTION As a Member of Engineering (Human Data), you will spearhead the development of sophisticated data labeling infrastructure supporting our large language models. This role encompasses building an internal labeling team, managing vendor relationships, and designing adaptive data annotation processes. While not customer-facing, your contributions are critical to our AI models' success, ensuring training on premium labeled datasets through crowdsourcing and advanced data collection methodologies. MISSION STATEMENT Construct and optimize scalable data labeling pipelines that drive machine learning model performance. CORE RESPONSIBILITIES - Design, implement, and expand scalable data labeling workflows integrated with model training systems - Manage internal labeling team growth and external vendor collaborations - Conduct experimental process improvements and quality assessment - Establish performance metrics and quality assurance protocols - Facilitate cross-functional alignment between research and engineering teams - Explore innovative tools to enhance labeling efficiency REQUIRED QUALIFICATIONS - Proven experience designing data labeling processes, emphasizing crowdsourcing solutions - Minimum 2 years technical experience in data engineering, data science, or project management - Expertise managing vendor and crowdsourcing platforms - Comprehensive understanding of data quality metrics - Ability to develop complex multi-stage annotation pipelines - Cloud platform familiarity preferred - Strong collaborative and independent problem-solving skills - Mandatory crowdsourcing platform experience INTERVIEW PROCESS - Initial consultation with CTO - Technical interviews with founding engineers - Team compatibility assessment - Final engineering team interview COMPREHENSIVE BENEFITS - Full remote work arrangement - 37 annual vacation/holiday days - Comprehensive health insurance - Equipment provision - Professional development allowances - Regular team gatherings - Inclusive, people-centric organizational culture