Senior Manager – AI/ML Data Operations
About the job
• *Company Description** iMerit is a premier AI data solutions provider, offering high-quality, end-to-end data labeling services across industries such as autonomous vehicles, agricultural AI, medical AI, geospatial, and financial services. With expertise in computer vision, natural language processing, and content services, iMerit delivers data that powers machine learning and artificial intelligence applications for Fortune 500 companies. Headquartered in the United States, iMerit operates globally with teams in the US, India, Bhutan, and Europe. Backed by investors like Omidyar Network, Dell.org, Khosla Ventures, and British International Investment, iMerit focuses on innovation, scalability, and quality in data solutions for diverse sectors. • *Role Overview** • ***The Senior Manager – AI/ML Data Operations will lead large-scale data annotation and AI training data programs supporting autonomous driving and advanced perception systems. The role oversees multi-project delivery, operational excellence, quality governance, and workforce strategy while working closely with global clients and leadership teams. • *Education Qualifications** • Bachelor’s Degree in Computer Science, Engineering, Data Science, or Management (Master’s preferred) • Preferred Certifications • PMP (Project Management Professional) • Agile / Scrum Certification • Six Sigma (Green Belt / Black Belt) • *Key Responsibilities** • Lead end-to-end delivery of AI/ML data operations programs for autonomous driving datasets. • Oversee multiple concurrent projects involving large-scale annotation teams. • Ensure delivery against SLAs, quality targets, and aggressive production timelines. • Build strategic partnerships with global automotive clients and customer success teams. • Act as escalation point for Tier-1 automotive OEMs and AV companies. • Drive continuous improvement initiatives for faster, cheaper, better outcomes. • Lead and mentor Project Managers, Team Leads, and annotation teams. • Implement quality assurance frameworks and conduct quality reviews. • Identify operational risks and implement mitigation strategies. • *Technical Expertise** • Multi-modal sensor knowledge including Camera, LiDAR point clouds, and 4D Radar. • Understanding of Sensor Fusion, Occlusion, Truncation, Ego-vehicle compensation, Temporal Tracking, and FPS synchronization. • Proficiency in Microsoft Excel (advanced), PowerPoint, Word, and Google Workspace. • *Communication & Leadership** • Exceptional verbal and written communication skills (CEFR C1 preferred). • Fluent in English with Tamil proficiency for workforce management. • Strong mentoring, coaching, and stakeholder presentation capabilities. • *What Success Looks Like** • Consistent delivery of high-quality AI training data programs. • Strong client satisfaction and program expansion. • Scalable workforce operations and productivity improvements. • High annotation accuracy and operational efficiency.
Requirements
- data labeling services
- AI/ML data operations
- project management
- multi-modal sensor knowledge
Qualifications
- Bachelor’s Degree in Computer Science, Engineering, Data Science, or Management
- Master’s preferred
Preferred Technologies
- data labeling services
- AI/ML data operations
- project management
- multi-modal sensor knowledge
About the company
iMerit is a premier AI data solutions provider, offering high-quality, end-to-end data labeling services across industries such as autonomous vehicles, agricultural AI, medical AI, geospatial, and financial services. With expertise in computer vision, natural language processing, and content services, iMerit delivers data that powers machine learning and artificial intelligence applications for Fortune 500 companies. Headquartered in the United States, iMerit operates globally with teams in the US, India, Bhutan, and Europe. Backed by investors like Omidyar Network, Dell.org, Khosla Ventures, and British International Investment, iMerit focuses on innovation, scalability, and quality in data solutions for diverse sectors.
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