3D Point Cloud Segmentation for Autonomous Navigation
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Summary
Developed and managed data annotation for 3D point cloud segmentation, critical for training autonomous navigation systems.
About
Highly accomplished Data Annotation Manager with a strong Computer Science background and proven expertise in scaling high-quality datasets for Computer Vision, NLP, and Multimodal AI. Adept at designing advanced workflows, QA pipelines, and annotation schemas aligned with MLOps ecosystems. Drives operational precision, cross-functional collaboration, and measurable AI model performance uplift through meticulous data quality management and team leadership.
Work
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Permanent
Summary
Leads scalable data annotation workflows for Computer Vision, NLP, and Multimodal AI, ensuring high-quality datasets and model alignment through expert QA/QC protocols, Human-in-the-Loop processes, and MLOps integrations.
Highlights
Directed large-scale data annotation pipelines for Computer Vision, NLP, and Multimodal AI projects, directly supporting SFT, RLHF, and HITL workflows to enhance AI model performance.
Implemented robust SOPs, QA, and QC protocols across diverse data formats, including bounding boxes, masks, 3D point clouds, OCR, and NER, ensuring data integrity and consistency.
Led and mentored multi-tier annotation teams, establishing feedback-driven QA loops that significantly improved data accuracy and team efficiency.
Ensured 100% SLA compliance and accurate export of labeled data in COCO, JSON, and Pascal VOC formats, streamlining data integration into MLOps pipelines.
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Permanent
Summary
Managed end-to-end data annotation project delivery, coordinating client requirements, technical execution, and quality assurance to ensure timely, high-quality outcomes aligned with operational standards.
Highlights
Spearheaded client engagement initiatives, defining project requirements and structuring workflows that resulted in successful delivery of multiple data annotation projects.
Developed comprehensive classification schemas, benchmark plans, and conducted demo reviews, significantly improving data quality and project accuracy.
Managed and optimized team training, enforced stringent Quality Control (QC) protocols, and monitored review pipelines, enhancing overall team productivity and data output quality.
Streamlined resource allocation across concurrent, high-volume projects, ensuring efficient delivery and meeting all project milestones within established timelines.
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Parmanent
Summary
Executed client assignments with precision, collaborating to enhance task quality and deliver high standards while supporting supervisory functions and streamlining workflows through advanced communication and productivity tools.
Highlights
Supervised operational output, directly contributing to increased task accuracy and overall project quality for client deliverables.
Produced client-ready deliverables using MS Office and G-Suite, improving reporting efficiency and presentation clarity.
Maintained high standards of efficiency and attention to detail, consistently exceeding client expectations and contributing to positive feedback.
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Summary
Contributed high-precision annotations to the Document Layout Analysis Project, supporting the digitization of Bengali language documents through accurate structural annotation and tool utilization.
Highlights
Produced high-precision annotations for Bengali documents within the Document Layout Analysis Project, contributing to efficient digitization efforts.
Utilized specialized tools like level box to ensure structural accuracy of annotations, meeting project deadlines and quality standards.
Education
Bangladesh University of Business Technology
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B.Sc.
Computer Science and Engineering
Alamdanga Govt. College
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Higher Secondary Certificate
General Studies
Awards
Super Star
Awarded By
Quantanite
Awarded for outstanding dedication and exceeding performance expectations.
Above & Beyond
Awarded By
Quantanite
Acknowledged for going above and beyond in fulfilling responsibilities and supporting team goals.
Employee of the Month
Awarded By
Quantigo AI
Recognized for exceptional performance and contributions to project success.
Languages
English
Bengali
Certificates
Project Management
Issued By
Coursera
Excel Essential Training (Microsoft 365)
Issued By
NASBA
Leveraging Generative AI for Project Management
Issued By
PMI
Conflict Management
Issued By
Quantigo AI
Data Annotation
Issued By
Quantigo AI
Skills
Cloud Platforms
AWS, GCP, Azure.
Agile Methodologies
Scrum Framework, Facilitation.
Project Management Tools
ClickUp, Asana, Trello.
Annotation Tools
Supervisely, Encord, SuperbAI, SuperAnnotate, V7, Roboflow, CVAT, Label Studio.
Collaboration Tools
Slack, Discord, Microsoft Teams.
Technical Documentation
Confluence, Google Office Suite.
Programming Languages
Python, JavaScript, SQL.
Version Control
Git, GitHub.
AI/ML Concepts
Computer Vision, Natural Language Processing (NLP), Multimodal AI, Generative AI, SFT (Supervised Fine-Tuning), RLHF (Reinforcement Learning from Human Feedback), HITL (Human-in-the-Loop), MLOps.
Data Formats & Protocols
Bounding Boxes, Masks, 3D Point Clouds, OCR, NER, COCO, JSON, Pascal VOC.
Quality Assurance
QA/QC Protocols, SOPs, Feedback-driven QA loops, SLA Compliance.
Projects
Multimodal Sentiment and Intent Classification – Banking Sector
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Summary
Contributed to data annotation efforts for multimodal sentiment and intent classification models tailored for the banking sector.
Reinforcement Learning with Human Feedback (RLHF) for Chatbot Optimization
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Summary
Participated in the data labeling and quality control for RLHF processes aimed at optimizing chatbot responses and performance.
Synthetic Dataset Curation for Multilingual LLM Training
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Summary
Involved in the curation and annotation of synthetic datasets for training multilingual Large Language Models (LLMs).
Adversarial Prompt Evaluation for Generative AI Safety
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Summary
Conducted adversarial prompt evaluation and data labeling to enhance the safety and robustness of Generative AI models.
Defect Detection for Aerial Vehicles
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Summary
Managed data annotation for defect detection systems in aerial vehicles, focusing on visual inspection data.
Naval Ship Docking Automation – Visual Tracking
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Summary
Contributed to visual tracking data annotation for automated naval ship docking systems.