Project Manager (Machine Learning, Autonomous Vehicles & ADAS) at Digital Divide Data

• Client Relationship & Communication Excellence
  • Build trusted relationships with ML, AV, and ADAS clients to ensure seamless service delivery.
  • Understand and articulate project scope, deliverables, timelines, and ownership.
  • Serve as the primary liaison for all client requests, updates, and issue resolution.
  • Track, manage, and close client requests with clarity, urgency, and professionalism.
  • Ensure workflows and outputs fully align with client expectations and technical guidelines.
•  Operational Delivery Ownership
  • Oversee day-to-day execution of annotation, QA, audits, and reporting activities.
  • Translate technical guidelines into clear, actionable workflows for delivery teams.
  • Monitor team adherence to SLAs/KPIs: accuracy, throughput, productivity, and latency.
  • Lead real-time issue resolution and ensure teams maintain context and operational readiness.
  • Maintain strict version control of instructions, guidelines, and workflow updates.
• Performance Tracking & Continuous Improvement
  • Track performance trends across ML/AV/ADAS datasets using scorecards and dashboards.
  • Diagnose quality or productivity gaps and implement root-cause fixes.
  • Partner with QA and Training teams to refine workflows, conduct refreshers, and clarify instructions.
  • Lead performance reporting to clients, highlighting insights, actions, and operational improvements.
• Team Leadership & Talent Development
  • Mentor and develop teams handling AI, CV, 3D, or LiDAR datasets.
  • Build a culture of feedback, technical excellence, and continuous learning.
  • Support team decision-making on ambiguous, complex, or escalated annotation scenarios.
  • Advise on capacity planning, calibration cycles, and training needs.
• Risk Management & Issue Mitigation
  • Identify risks related to workflow complexity, guideline ambiguity, tooling inefficiencies, or data quality concerns.
  • Develop mitigation strategies to ensure delivery continuity and client satisfaction.
  • Support Business Continuity Plans (BCP) and drive readiness for activation.
  • Escalate advanced risks to senior leaders and product teams for resolution.

 What You’ll Bring

Education & Experience

• Bachelor’s degree in Data/AI, Computer Science, Engineering, Information Systems, or related fields.
• 5+ years of experience in AI/ML operations, project management, or technical workflow coordination.
• Hands-on exposure to annotation workflows: 2D/3D CV, LiDAR, ADAS, or AV datasets.
• Strong track record managing projects in KPI-driven environments.

Technical & Domain Knowledge

• Familiarity with annotation tools such as CVAT, SuperAnnotate, and Labelbox.
• Understanding of ML metrics, data quality principles, and AV/ADAS ecosystems.