Position Overview: We are seeking a dynamic and results-driven Sr. Delivery Manager with over 15 years of experience in managing large-scale delivery projects to oversee the successful execution of data annotation initiatives. This role will manage a team of 300+ annotators and collaborate with cross-functional teams to ensure data integrity, optimize internal processes, and deliver high-quality results consistently. The ideal candidate will have a strong technical background, proven leadership skills, and a passion for innovation in AI and machine learning, with specific expertise in Python, multimodality, and mathematical analysis.Primary Responsibilities:1. Team Leadership and DevelopmentLead, mentor, and develop a large team of annotators, ensuring they meet and exceed project goals.Conduct performance analyses, identify areas for improvement, and implement targeted training initiatives.Foster a culture of excellence, continuous learning, and employee engagement through development programs and performance reviews.Develop and implement strategies, including gamification, to motivate and recognize high-performing team members.2. Project Management and CoordinationCollaborate with cross-functional teams (XFN) to define, refine, and communicate project scope, objectives, and quality control guidelines.Develop accurate project timelines, prioritize tasks, and allocate resources to ensure timely delivery of high-quality outputs.Identify and address project blockers, adjusting resources and strategies as needed to meet project deadlines.Maintain active communication with stakeholders, providing regular updates on project progress, challenges, and solutions.3. Data Quality and IntegrityDive deep into the data annotation process to understand and address inefficiencies and ensure the highest level of data integrity.Analyze data sets and evaluation results to identify key findings, trends, and anomalies, and communicate actionable insights to relevant teams.Ensure the security and integrity of data throughout the annotation lifecycle.Share best practices and lessons learned with the team to promote continuous improvement in data quality and annotation processes.4. Technical Collaboration and InnovationWork closely with technical teams to develop, refine, and optimize internal tooling that supports efficient and accurate data annotation.Stay informed of industry trends, emerging technologies, and best practices in AI, machine learning, and multimodal data processing.Contribute to the development and implementation of innovative strategies to reduce task completion times and improve overall efficiency.Oversee the creation and maintenance of documentation for technical processes, guidelines, and training materials.Secondary Responsibilities:Stakeholder Management:Build and maintain strong relationships with stakeholders across the organization to ensure alignment on project goals and expectations.Communicate complex technical concepts to both technical and non-technical stakeholders clearly and effectively.Continuous Improvement:Foster a culture of continuous improvement, encouraging the team to proactively identify and implement process enhancements.Lead initiatives to incorporate feedback, lessons learned, and industry best practices into the team's workflows.Strategic Planning:Collaborate with senior leadership to develop and implement long-term strategies for the data annotation team, aligned with organizational goals.Identify opportunities for growth and expansion within the team's capabilities, contributing to the overall success of the organization.Required Skills and Qualifications:15+ years of experience in project delivery, with a proven track record of successfully managing large-scale projects and teams.Bachelor's degree in a relevant field (e.g., Computer Science, Data Science, Mathematics, AI, or related disciplines).Proven leadership experience managing large teams, with a strong track record of developing high-performing teams.Deep technical expertise in AI, machine learning concepts, and multimodal data processing.Proficiency in Python for data analysis, tool development, and process automation.Strong mathematical skills, with the ability to apply advanced mathematical concepts to data analysis and problem-solving.Extensive experience in data curation, annotation, and quality control processes.Strong analytical skills, with the ability to analyze data sets, identify trends, and provide actionable insights.Excellent communication skills, capable of effectively conveying technical concepts to diverse audiences.Detail-oriented with a strong focus on delivering high-quality outputs and maintaining rigorous quality standards.Experience in creating and maintaining documentation for technical processes and training materials.Passionate about AI, data integrity, and leading teams to success.Preferred Skills and Qualifications:Advanced degree in a relevant field.Experience with gamification strategies to drive team motivation and performance.Familiarity with project management tools and methodologies.Knowledge of the latest multimodal AI technologies and how they can be leveraged to improve data annotation processes.
