Project Manager (Machine Learning, Autonomous Vehicles & ADAS)

Company Description

Digital Divide Data (DDD) is a BPO that delivers ML data solutions and content services to Fortune 500 companies and the world’s leading academic institutions. DDD is unique in its ability to deliver end-to-end data creation, curation, labeling, and annotation services, regardless of scale, with a guaranteed level of quality.

Job Description

Lead the Future of AI, Autonomous Systems, and High-Performance Data Delivery

Digital Divide Data (DDD) is a global leader in powering Machine Learning, and Autonomous Systems with high-quality, large-scale data. We are seeking a Project Manager (ML, AV & ADAS) who will own delivery excellence, elevate operational performance, and drive client success across cutting-edge AI programs.

If you excel at orchestrating teams, managing complex workflows, solving operational challenges, and communicating confidently with clients, this role is your runway to impact the future of autonomous intelligence.

Your Mission — What You’ll Lead

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.

Qualifications

What You’ll Bring

Education & Experience

• Bachelor’s degree in Data/AI, Computer Science, Engineering, Information Systems, or related fields.

• 3–5 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.

Additional Information

Why Join DDD?

• Work at the cutting edge of global AI innovation.

• Collaborate with cross-functional technical teams solving real-world problems.

• Grow your leadership, technical, and analytics skills in a mission-driven organization.

• Help shape the datasets that power next-generation AI systems.