Hi, I’m Dawood Tahir, a certified Machine Learning Engineer with over 2 years of experience in computer vision and AI projects. I specialize in transforming complex data into actionable insights through real-time analytics and innovative solutions, such as real-time traffic analytics pipelines, YOLOv8-based detection, and multi-vehicle tracking. I’m passionate about building scalable ML systems that deliver measurable impact. I have a proven track record of leveraging AWS technology to deploy AI applications and empowering teams with robust, production-ready solutions. I aim to elevate efficiency and accuracy for forward-thinking organizations and contribute to high-impact projects in AI and computer vision.

Dawood Tahir

Hi, I’m Dawood Tahir, a certified Machine Learning Engineer with over 2 years of experience in computer vision and AI projects. I specialize in transforming complex data into actionable insights through real-time analytics and innovative solutions, such as real-time traffic analytics pipelines, YOLOv8-based detection, and multi-vehicle tracking. I’m passionate about building scalable ML systems that deliver measurable impact. I have a proven track record of leveraging AWS technology to deploy AI applications and empowering teams with robust, production-ready solutions. I aim to elevate efficiency and accuracy for forward-thinking organizations and contribute to high-impact projects in AI and computer vision.

Available to hire

Hi, I’m Dawood Tahir, a certified Machine Learning Engineer with over 2 years of experience in computer vision and AI projects. I specialize in transforming complex data into actionable insights through real-time analytics and innovative solutions, such as real-time traffic analytics pipelines, YOLOv8-based detection, and multi-vehicle tracking. I’m passionate about building scalable ML systems that deliver measurable impact.

I have a proven track record of leveraging AWS technology to deploy AI applications and empowering teams with robust, production-ready solutions. I aim to elevate efficiency and accuracy for forward-thinking organizations and contribute to high-impact projects in AI and computer vision.

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Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
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Language

English
Fluent

Work Experience

Data Scientist at Psi-Square
September 30, 2024 - July 21, 2025
Developed a computer vision project that calculates traffic dwell duration in zones for live video feeds employing system clocks instead of FPS. Utilized Roboflow's ByteTrack for multi-car tracking without latency. Researched and developed a football players and pitch detection project using YOLOv8 for players detection and UMAP for dimensionality reduction, applying 2D ball tracking through pitch key point transformations resulting in a game-like detection end product. Implemented Multi-Agent RAG harnessing langGraph for academic research with WebResearch, PaperScraper, and Evaluator agents to improve answer accuracy.
AI Engineer at OMNO AI
February 28, 2024 - July 21, 2025
Developed a vehicle speed estimation project for a highway using a single camera sensor, processing live video streams with AWS Kinesis and AWS Lambda to match frame rates for a custom car detection model. Applied a transformation matrix to convert 3D points to 2D for speed calculation accuracy. Utilized AWS EC2 to deploy and scale an AI ad creation app scraping brand websites for text and imagery, leveraging LLM agents to extract marketing text and generative AI to produce ad banners. Conducted research and development of face authentication using NIR camera and PointNet++, and developed a mobile receptionist robot with speech recognition, interaction capabilities, gesture detection, and robot motion controls.
ML Engineer at Academic/Research Project (Robotics, AI & Autonomous Systems)
May 1, 2023 - April 1, 2024
Built an end-to-end forecasting solution using Prophet and LSTM baselines, integrating holiday features, promo-impact variables, and weather-like regressors. Achieved 14% reduction in MAPE and produced a production-ready forecast workflow with interpretable drivers for inventory and staffing decisions.
ML Engineer / AI Researcher at City, University of London – Robotics, AI & Autonomous Systems Lab
October 1, 2024 - Present
Developed a fraud-detection pipeline on Databricks using SQL for large-scale feature extraction and window-based behavioral signals; performed exploratory profiling on 20M+ transactions and trained an optimized XG Boost model. Conducted multi-agent RAG harnessing Graph for academic research. Built end-to-end fraud-detection workflow and prepared actionable insights for stakeholders.
ML Engineer / Data Scientist at Psi-Square, Lahore; CodeLens Ltd, London
May 1, 2023 - April 1, 2024
Built an end-to-end forecasting solution using Prophet and LSTM baselines, integrating holiday features, promo-impact variables, and weather-linked regressors. Achieved a 14% reduction in MAPE and produced a production-ready forecast workflow with interpretable drivers for inventory and staffing decisions. Performed structured data exploration on 50k+ telecom customer records. Engineered predictive features (tenure buckets, contract risk score, payment irregularity index) and trained Gradient Boosting and Random Forest models, improving recall on high-risk customers by 18%. Delivered a deployable inference pipeline and clear stakeholder insights on actionable retention levers.
AI Research / Fraud Detection & Data Science Project
October 1, 2024 - Present
Built an end-to-end fraud detection pipeline on Databricks using SQL for large-scale feature extraction and window-based behavioral signals; performed exploratory profiling on 20M+ transactions; trained an optimized XGBoost model with class-imbalance handling, improving precision on high-risk customers by 22% and delivering a production-ready workflow. Developed Web Research Agent, Paper Scraper Agent, and Evaluator Agent workflows to surface answers from user-provided research papers. Led a Face Authentication PoC using a NIR camera for depth imaging to mimic state-of-the-art smartphone unlocking techniques via embedding vectors (PointNet++).
Data Scientist at Psi-Square, Lahore
January 1, 2019 - January 1, 2023
KPI modelling, product evaluation, deep reinforcement learning, and ML engineering projects; early-stage data science work spanning feature engineering, model development, and deployment.
Data Scientist at CodeLens LTD
May 1, 2023 - April 1, 2024
Built an end-to-end forecasting solution using Prophet and LSTM baselines, integrating holiday features, promo-impact variables, and weather-linked regressors. Achieved a 14% reduction in MAPE and produced production-ready forecast workflows with interpretable drivers for inventory and staffing decisions. Performed structured data exploration on 50k+ telecom customer records; engineered predictive features (tenure buckets, contract risk score, payment irregularity index) and trained Gradient Boosting and Random Forest models, improving recall on high-risk customers by 18% and delivering a scalable, production-ready workflow.
ML Engineer at CodeLens LTD
October 1, 2024 - Present
Built an end-to-end fraud detection pipeline on Databricks using SQL for large-scale feature extraction and window-based behavioral signals; conducted exploratory profiling and delivered a production-ready workflow. Developed a data-driven research workflow to extract brand-text and imagery details from websites, and designed a RAG-based inference flow to support action-oriented insights.
Machine Learning Engineer at CodeLens
September 1, 2024 - Present
Researched and developed a football analytics pipeline for player and pitch understanding. Trained a YOLOv8 detector to identify players from two teams. Estimated 2D ball positions using pitch keypoint-based holography, producing a game-like end product that visualises players and ball possession over time. Evaluated the system using [email protected] and tracking accuracy to be 77%.
AI Engineer at OMNO AI
May 1, 2023 - February 1, 2024
Successfully improved RAG chunks by creating hierarchical clusters of chunks. Started from a base node and chunks, to calculate embeddings between simultaneous chunks and moving down the tree in the same way. This helped the final customer bot be more relevant in answering questions. Implemented a multi-agent LLM research system with integrated voice-model interaction, secured via AWS Cognito and backed by Aurora for persistent conversation history. Implemented a Graph-RAG reasoning model for complex relationship-aware retrieval.

Education

BSc at UET, Lahore
January 1, 2019 - December 31, 2023
BSc Mechatronics Engineering at UET Lahore
January 1, 2019 - January 1, 2023
Bachelor of Science in Mechatronics Engineering at University of Engineering and Technology, Lahore
January 1, 2019 - January 1, 2023
BSc Mechatronics Engineering at University of Engineering & Technology, Lahore (UET Lahore)
January 11, 2030 - December 7, 2025
MSc in Robotics, AI & Autonomous Systems at City, University of London
September 1, 2024 - October 1, 2025
BSc in Mechatronics Engineering at University of Engineering & Technology (UET) Lahore
October 1, 2019 - May 1, 2023

Qualifications

AWS, Associate ML Engineer
January 1, 2023 - December 31, 2023
Brainiac ML Competition Prize
May 1, 2023 - December 7, 2025
Certified ML Engineer
January 1, 2019 - January 1, 2023
ML Engineer Certification
January 1, 2019 - January 1, 2023
AWS Certified Machine Learning - Associate
September 1, 2025 - December 7, 2025

Industry Experience

Software & Internet, Computers & Electronics, Transportation & Logistics, Manufacturing, Professional Services, Media & Entertainment, Education, Telecommunications, Other