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Supervisor, AI-ML Data Annotation (AV/ADAS)

Digital Divide Data Kenya Full Time Posted 2026-08-25

CountyNairobiCityNot specifiedContractFull TimePosted2026-08-25Close dateNot specifiedExperience3 yearsSourceMyJobMag Kenya

AI-ML Data AnnotationAV ADASSupervisorNairobiFull TimeOnsiteData AnnotationOperations SupervisionBPOICTinternshipentregador

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AI summary

Digital Divide Data is hiring a Supervisor, AI-ML Data Annotation (AV/ADAS) in Nairobi to lead daily production operations for AI/ML data annotation programs focused on Autonomous Vehicle and ADAS projects. The role involves supervising delivery teams, managing performance against SLAs and KPIs, and driving process and quality improvements. Candidates need 3 years of experience and a diploma or degree in a relevant field.

Frontline leadership role in AI/ML data annotation for AV/ADAS programs
Requires 3 years of experience and BA/BSc/HND or Diploma
Full-time, onsite position based in Nairobi
Focus on ADAS taxonomy, 3D semantic segmentation, LiDAR labeling, and telemetry analytics
Involves team supervision, performance management, and continuous improvement

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Original source description

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DDD delivers high-quality, competitively priced business process outsourcing (BPO) solutions to clients worldwide. At the same time, DDD’s innovative social model enables talent from underserved populations to access professional opportunities and earn lasting higher income, including youth from low-income families in developing countries, as well as m...

Experience

3 years
Location
Nairobi
Job Field
Data, Business Analysis and AI
,
ICT / Computer
Position Summary
We are seeking an experienced and highly capable
Supervisor, AI-ML Data Annotation
to lead daily production operations supporting complex AI/ML data annotation programs, with a strong focus on the
Autonomous Vehicle (AV) and ADAS domain
. This role is responsible for supervising delivery teams, driving workforce performance, ensuring compliance with quality and service standards, and advancing operational excellence across client programs.
The successful candidate will bring strong expertise in
AI-ML data annotation workflows
, deep familiarity with
ADAS behavioral taxonomy, advanced 3D semantic segmentation, LiDAR labeling, and telemetry data analytics
, and proven success supervising teams in a production-driven environment. This is a critical frontline leadership role for a professional who can effectively balance client delivery expectations, people management, process discipline, and continuous improvement.
Key
Minimum of 3
years’
in a BPO environment
.
Minimum of 2-3
years’
supporting AI/ML data annotation projects
, preferably within the
Autonomous Vehicle (AV) or ADAS industry
.
Prior
in a
supervisory or people-management role is mandatory
.
Demonstrated
managing team performance, quality outcomes, productivity, utilization, service levels and delivery targets.
leading production teams in a structured, high-volume and client-driven environment.
Practical knowledge of performance management, employee coaching, workflow monitoring and operational reporting.
Check how your CV aligns with this job
Method of Application
Interested and qualified? Go to
Digital Divide Data on smrtr.io
to apply
Build your CV for free.
Download in different templates.

Responsibilities

Operational Supervision
Supervise the daily activities of the client delivery team to ensure efficient execution of assigned workflows and achievement of operational targets.
Maintain full accountability for team-level performance against
SLAs, KPIs, productivity, quality standards, and operational risk controls
.
Monitor workflow performance, identify delivery risks, and take timely action to maintain continuity, efficiency, and service excellence.
Serve as the first point of internal escalation for project-related issues and ensure prompt escalation to relevant stakeholders where appropriate.
Monitor project and workflow systems and applications to ensure they are functioning properly and supporting delivery requirements.
Track, analyze, and report on project, operational, and people-related metrics to support performance management and decision-making.
People Supervision and Performance Management
Directly supervise production employees, including coaching, performance evaluation, goal setting, performance improvement plans, and disciplinary action as required.
Provide day-to-day direction, guidance, and support to team members to ensure clarity of expectations and consistency of execution.
Conduct regular performance discussions to review results, recognize achievements, and identify opportunities for improvement and development.
Coordinate and/or deliver training to strengthen team capability, close performance gaps, and support continuous improvement.
Support workforce planning decisions, including staffing input, resource utilization, and workload balancing.
Own team-level conflict resolution and contribute to a productive, engaged, and accountable work environment.
Continuous Improvement and Delivery Excellence
Analyze operational data and workflow processes to identify inefficiencies, recurring issues, and opportunities for performance improvement.
Conduct root cause analysis (RCA) and recommend corrective and preventive actions to address quality, productivity, or delivery challenges.
Provide recommendations on process improvements, operational initiatives, and workflow enhancements that strengthen service delivery.
Identify opportunities for AI-driven automation and optimization to improve operational efficiency and accuracy.
Act as a liaison between the delivery team and management, providing regular feedback on performance trends, challenges, and improvement opportunities.
Manage workforce productivity and utilization effectively to support achievement of delivery and financial cost targets.
Qualifications
Additional Information
Bachelor’s degree preferred.
A college diploma or relevant professional certification will also be considered.

Source and provenanceSource: MyJobMag Kenya. Last checked: 2026-09-16.Kazi Connect is a job discovery service, not the employer. Always confirm the vacancy at the original source.Summaries may be AI-assisted. Report inaccurate content.

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