Question
Contract
2-5

Manager, Operations (Machine Learning, Autonomous Vehicles & ADAS)

4/22/2026

The Operations Manager will oversee the delivery of high-quality machine learning and autonomous vehicle data projects while managing client relationships and communication. They are responsible for optimizing operational workflows, monitoring performance metrics, and leading teams to ensure project accuracy and productivity.

Working Hours

40 hours/week

Company Size

1,001-5,000 employees

Language

English

Visa Sponsorship

No

About The Company
DDD provides ML data operations support with Human-in-the-loop for LLMs and autonomous systems, focusing on AI/ML model training and annotation services. Trusted by Fortune 500 companies and pioneers in the autonomy industry, government, defense tech, technology, AgTech, and cultural heritage, we ensure the safety and performance of AI applications. DDD offers end-to-end AI and autonomy solutions, supporting the entire lifecycle of autonomous systems from development and deployment to market readiness. We provide solutions in fleet operations, navigation maps, ML model development, data analytics, simulation, Operational Design Domain (ODD) analysis, scenario dataset creation, and product verification and validation (V&V). DDD’s Generative AI solutions accelerate innovation by providing high-quality NLP dataset creation, prompt engineering, and model output evaluation. Our expertise ensures optimal model performance through red teaming, reinforcement learning, fine-tuning, and rigorous quality control, empowering AI systems to learn effectively and generate accurate, reliable results. At the same time, DDD’s unique Impact Sourcing model established in 2001, provides talented youth from low-income backgrounds with access to professional opportunities. This initiative enables them to pursue higher education while gaining real-world work experience, ultimately increasing their lifetime earnings. Since its inception, DDD’s program has helped young professionals in Cambodia, Laos, and Kenya earn a projected total of more than $250 million in additional income. Over the years, DDD has earned global recognition for its innovation, service excellence, and social impact. We have received the Global Sourcing Council’s 3S Award for Sustainable and Socially Responsible Sourcing and the Google Award for Innovation in Business Process Outsourcing (BPO). Additionally, The Global Journal has consistently ranked DDD among the Top 100 NGOs worldwide.
About the Role

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 an Operations 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.
  • A minimum of 2.5 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.
  • Must have worked in a BPO

Additional Information

  • Familiarity with annotation tools such as CVAT, SuperAnnotate, and Labelbox.
  • Understanding of ML metrics, data quality principles, and AV/ADAS ecosystems.
Key Skills
Machine LearningAutonomous VehiclesADASProject ManagementData AnnotationComputer VisionLiDARWorkflow OptimizationKPI TrackingClient Relationship ManagementQuality AssuranceTechnical LeadershipCVATSuperAnnotateLabelboxData Analysis
Categories
Management & LeadershipData & AnalyticsTechnologyEngineeringSoftware
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