Technical Leads LATAM

Their day to day includes overseeing data annotation teams and workflows to maintain the highest levels of dataset integrity and quality. This will primarily involve auditing annotation outputs, onboarding and mentoring new hires, and analyzing datasets to identify trends or anomalies. This person must be able to translate complex technical concepts, manage project timelines, and provide data-driven insights to improve the internal annotation platform. Finding those who are sharp, highly analytical, and can bridge the gap between technical workflows and team performance would be a great fit for the role! Data architecture and workflow optimization are a huge plus!

Day to Day Responsibilities: Assist in overseeing both the existing data annotation team and new hires. Support project management activities, including new hire onboarding and performance monitoring. Contribute technical feedback to aid in the development of the internal annotation platform and data annotation workflows. Provide guidance, training, and knowledge transfer to data annotators to maximize performance. Conduct or audit Quality Assurance (QA) processes to ensure dataset consistency and high quality. Support the interviewing of data annotators and assist with project onboarding. Proactively identify challenges and trends, and suggest effective solutions for data quality, throughput, and resource allocation issues. Maintain detailed documentation of annotation processes, procedures, and best practices. Generate reports on key performance metrics and provide data-driven insights for decision-making.

Must Haves: Bachelor’s Degree required. Open major, provided the academic background demonstrates high-level critical thinking, synthesis, and reading comprehension (e.g., Translation, Law, Psychology, Marketing, or Humanities) 2-3 years of data annotation or LLM evaluation experience (Textual data annotation preferred) Some experience with Quality Auditing (QA) Demonstrated expertise in data quality, labeling processes, and maintaining high data integrity. Excellent analytical skills, with the ability to analyze data sets, identify trends and anomalies, and provide insights that drive project improvements. Proven ability to manage tasks independently and contribute effectively to team goals. Strong communication skills for articulating technical concepts to both technical and non-technical audiences. Plusses: Experience with SQL and Python for data manipulation Experience designing or optimizing internal data annotation workflows and interfaces Advanced background in throughput tracking and resource allocation management Experience creating case studies to analyze and improve labeling methodologies. Experience interviewing