Mohammed Azhar

Autonomous Vehicle Validation Lead with 4+ years of experience in ADAS, Autonomous Driving, Computer Vision, and AI/ML data operations. Experienced in leading 30+ member teams, managing KPI-driven validation workflows, QA triage, and end-to-end autonomous driving testing in production environments. Strong expertise in Perception, Prediction, and Planning system validation, LiDAR analysis, localization testing, scenario-based evaluation, and Root Cause Analysis (RCA).

Skilled in HITL-based annotation workflows and multi-sensor validation for autonomous driving systems.

Team Lead – Autonomous Vehicle Validation (Level 4 ADAS) - Tata Elxsi Ltd. | Arctictern Solutions Pvt. Ltd. - Bangalore

(2026-03 - 2026-06)

• Led a team of 30 analysts for autonomous vehicle validation, simulation, and scenario-based testing.
• Managed KPI-driven validation workflows and ensured 95–98% quality consistency across deliverables.
• Improved team productivity by ~10–15% through workflow optimization and RCA-driven continuous improvements.
• Executed validation of complex autonomous driving scenarios including VRU, PUDO, construction zones, junctions, and emergency cases.
• Performed Perception, Prediction, and Planning system analysis including FP/FN/TP/TN evaluation.
• Conducted LiDAR validation, localization assessment, ZRN verification, ZPT behavioral analysis, and teleoperation reviews.
• Drove RCA-based improvements to reduce recurring issues and improve validation efficiency.
• Mentored team members and ensured consistent validation quality and reporting standards.

Annotation Engineer (Computer Vision) - Xeedo Technologies (Sony Software Centre India Pvt. Ltd.) - Bangalore

(2025-06 - 2026-03)

• Performed image and video annotation using bounding boxes, polygons, and keypoints for computer vision datasets.
• Worked on production ADAS dataset annotation and validation using CVAT, Fast Label, and Jira workflows.
• Supported multi-sensor labeling workflows for autonomous driving and AI/ML training pipelines.
• Ensured dataset consistency and quality across validation cycles and QA reviews.
• Collaborated with QA and engineering teams for dataset correction and improvement workflows.

Process Executive - Randstad India Pvt. Ltd. | NVIDIA Graphics Pvt. Ltd. - Hyderabad

(2021-04 - 2024-08)

• Worked as Subject Matter Expert (SME), Trainer, and Quality Analyst for ADAS data operations in autonomous driving projects.
• Contributed to production-level ADAS perception, prediction, and planning validation workflows.
• Performed multi-sensor annotation including image, video, and LiDAR labeling for autonomous driving systems.
• Executed lane marking, object detection, and sensor data validation across ADAS pipelines.
• Provided training and guidance to team members on annotation standards and quality best practices.
• Conducted quality audits and ensured consistency in dataset accuracy across HITL workflows.
• Supported scenario-based testing for Perception, Prediction, and Planning modules.
• Participated in dataset refinement and QA cycles for autonomous driving systems.
• Generated business intelligence reports and supported operational insights for stakeholders.

Bachelor of Technology - Mechanical Engineering - Audisankara College of Engineering (2014-09 - 2018-05)