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

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

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.