Digital Divide Data
Jobs at Digital Divide Data
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Recently posted jobs
Artificial Intelligence • Computer Vision • Machine Learning • Natural Language Processing
Supervise daily HR operations, including recruitment, onboarding, contracts, payroll, performance reviews, employee relations, grievance and disciplinary processes, workplace safety, injury claims, HRIS administration, and confidential employee records. Ensure compliance with Kenyan labor laws, data protection requirements, WIBA, and occupational health and safety standards while supporting employee welfare and accurate management reporting.
Artificial Intelligence • Computer Vision • Machine Learning • Natural Language Processing
Data Labelers annotate autonomous vehicle and ADAS data, including LiDAR point clouds, 2D/3D bounding boxes, images, video, objects, lanes, roads, pedestrians, and vehicles. They apply detailed annotation guidelines, perform quality assurance, complete language-based tasks, and meet productivity and accuracy standards. Successful candidates attend an 80-hour in-person boot camp in Nairobi, complete assessments, and may join a pre-qualified talent bench for future project assignments.
Artificial Intelligence • Computer Vision • Machine Learning • Natural Language Processing
Leads the company’s IT strategy, infrastructure, service management, cybersecurity, compliance, disaster recovery, and vendor relationships. Oversees IT systems and service delivery, develops policies and governance practices, manages risks and business continuity, and partners with stakeholders to implement technology solutions. Builds and mentors the IT team, manages budgets and resources, and drives continuous improvement and digital transformation.
Artificial Intelligence • Computer Vision • Machine Learning • Natural Language Processing
Executes 2D and 3D LiDAR annotation and segmentation according to SOPs, taxonomies, quality standards, and productivity targets. Maintains accurate object classification, identifies labeling errors and tool issues, escalates quality risks, documents problems, and suggests workflow improvements. Collaborates with peers, QA teams, and stakeholders in English while sustaining consistent performance in repetitive, high-volume production workflows.



