Expert Team Lead, SWE
Jobgether
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an Expert Team Lead, SWE based in Canada. This is a hands-on leadership opportunity focused on building and maintaining high-quality human-generated data that supports advanced AI model development. You will lead a team of AI Tutors while remaining directly involved in reviewing, evaluating, and improving technical work. The role combines people leadership, data quality, operational excellence, and software engineering expertise. You will establish quality standards, monitor performance, identify bottlenecks, and introduce scalable improvements. Working closely with data and engineering stakeholders, you will translate evolving model requirements into effective data and evaluation strategies. The environment is fast-paced, collaborative, highly autonomous, and designed for people who thrive on challenging technical problems and continuous improvement. Accountabilities: - Own end-to-end quality and delivery for assigned human data projects, personally reviewing technical work and ensuring accuracy, consistency, guideline adherence, and reliable data production at scale. - Lead, coach, and performance-manage a team of AI Tutors, including conducting performance reviews, maintaining development records, creating improvement plans, facilitating shadow sessions, and supporting ongoing professional development. - Participate directly in labeling, annotation, evaluation, and review activities to maintain high standards and demonstrate best practices. - Establish and enforce quality assurance processes, taxonomy standards, workflow guidelines, and evaluation criteria. - Monitor operational KPIs such as quality scores, throughput, and send-back rates, using performance data to identify bottlenecks and improve team efficiency. - Develop and maintain training materials, practice exercises, and certification benchmarks while managing certification processes and workforce adjustments.
- Partner with data managers, other team leads, and engineering stakeholders to translate AI model requirements into clear labeling strategies and operational processes. - Foster a high-performance culture through effective coaching, accountability, talent development, and appropriate performance-management actions. - Document project outcomes, identify opportunities for process iteration, and communicate project status, risks, and results to relevant stakeholders. - Represent the needs and perspectives of the AI Tutor team while promoting strong collaboration across the wider human data organization. Requirements: - 1+ years of hands-on experience in data labeling, annotation, AI training or evaluation, content quality, or a comparable operational discipline. - Professional experience building or contributing to scalable, high-performance technology applications, particularly in software engineering or another technical environment. - Demonstrated understanding of data quality metrics, annotation workflows, guideline-driven processes, and quality assurance practices. - Basic knowledge of artificial intelligence and machine learning concepts, including how high-quality training and evaluation data influences model performance. - Experience with people management, coaching, training-program development, performance management, or certification frameworks. - Previous experience leading small teams in data labeling, annotation, technical operations, or related environments is strongly preferred. - Ability to manage multiple projects simultaneously, prioritize effectively, and operate successfully in a fast-moving environment. - Strong analytical capabilities and familiarity with KPI-driven operational improvement; SQL experience is a plus. - Experience working with distributed teams or mixed employment models, including full-time employees and contractors, is advantageous.
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