Mohammed Zamasheer A M

Directed large-scale ADAS data collection and annotation operations for Uber's Moonshot autonomous driving initiative, ensuring high-quality data for perception model development.

Managed end-to-end data workflows, encompassing sensor data capture (camera, LiDAR, radar, GPS) and labeling, to support critical AI development.

Supervised multi-tier annotation teams of over 200 members and 5 team leads, consistently delivering high-quality labeled datasets on time.

Partnered with R&D, data science, and engineering teams to define data requirements, annotation standards, and quality metrics, ensuring alignment with project goals.

Implemented process optimization and automation strategies, significantly improving annotation accuracy and reducing turnaround time for data processing.

Drove continuous improvement in data quality, enabling better model performance and faster deployment of autonomous systems.

Successfully scaled operations from pilot to full production, supporting the rapid growth of Uber's autonomous vehicle R&D efforts.

Led operations for large-scale data annotation projects in the computer vision domain, overseeing a workforce of over 200 members and 5 team leads.

Collaborated effectively with project managers and QA teams to consistently achieve and maintain critical client KPIs.

Conducted performance reviews, training sessions, and one-on-one mentorship, significantly enhancing overall team productivity.

Implemented efficient workflows and tracked project milestones, ensuring timely delivery and maintaining robust stakeholder communication.

Successfully scaled the project from pilot to full-scale within tight deadlines, demonstrating strong project management and execution.

Demonstrated expertise in Advanced Driver-Assistance Systems (ADAS) calibration, configuring and calibrating systems to meet high safety standards.

Directed critical data annotation projects, including Landmark, Seat Occupancy, and Tyre Annotation, for AI model recognition and development.

Utilized advanced annotation tools and worked with 2D and 3D datasets to ensure precise contextual identification and accurate labeling across diverse data types (images, videos, LiDAR, segmented data).

Conducted rigorous QA checks and implemented protocols to identify and rectify discrepancies, significantly enhancing model training accuracy.

Led training and development programs for junior annotators, designing instructional sessions and establishing quality standards to enhance team proficiency and consistent performance.

Contributed to the creation and refinement of internal documentation and standardized procedures, improving data processing speed and accuracy, enabling consistent deadline achievement.

Collaborated cross-functionally with data scientists, engineers, and product teams to clarify project requirements and provide insights on dataset quality, ensuring successful model outcomes.

Collaborated with hiring managers to define precise job requirements and candidate profiles, streamlining the initial stages of the recruitment process.

Utilized applicant tracking systems to efficiently manage candidate applications and communications, improving recruitment workflow.

Screened a high volume of resumes to identify qualified candidates, significantly contributing to a diverse talent pool.

Coordinated complex interview schedules between candidates and hiring teams, ensuring smooth and timely progression of interviews.

Developed compelling job postings aligned with company culture and values, enhancing employer brand appeal.

Negotiated employment offers with selected candidates and conducted initial phone screens, successfully securing top talent.

Accurately annotated diverse datasets for training AI models, directly contributing to improved model accuracy.

Conducted thorough reviews and verifications of annotations, ensuring consistency and high-quality control.

Collaborated with team members to refine annotation guidelines and processes, enhancing overall data quality and efficiency.

Utilized various annotation tools to effectively label images, text, and audio data, supporting AI development initiatives.

Assisted in resolving annotation-related queries from team members, ensuring smooth workflow and knowledge transfer.

Worked with cross-functional teams to achieve project goals, demonstrating strong collaborative skills.