Fahim Rahman - ML Engineer
+971 562-074-075 — # rahmanbinfaruq@outlook.com — ï linkedin.com/in/rahmanbinfaruq — § github.com/AlgRizmiCE780
Technical Skills
– Programming Languages: Python, C++, SQL
– Computer Vision: OpenCV, YOLOv5/v8, Detectron2, MiDaS, MediaPipe
– Deep Learning: PyTorch, TensorFlow, Keras, ONNX, TensorFlow Lite
– Model Optimization: Quantization, Pruning, TensorRT
– Deployment: Flask, FastAPI, Docker, Android (via ONNX/TFLite)
– Data Handling: NumPy, Pandas, torchvision
– Annotation & Labeling Tools: CVAT, Roboflow, LabelImg
– Visualization: Matplotlib, Seaborn, TensorBoard
– Development Tools: Git, Linux/Unix, Bash, Jupyter Notebook, Google Colab
Experience
Assuretech Business Solutions, Trivandrum September 2023 – April 2025
Junior Software Engineer
Dubai Insurance(ML + .net)
– .NET MVC backend system with RESTful APIs to automate party profile replication, cutting manual entry by 70%.
– Built and deployed a machine learning recommendation engine (Python, Random Forest) that analyzed broker data
(type, sector, location) with 92% accuracy via a Flask API hosted on Azure—achieved sub-200ms latency and improved
onboarding recommendations.
– Integrated Redis caching and Azure Service Bus to scale throughput by 60% and reduce error rates by 45%.
Takaful Emirate
– Responsible for developing a custom middleware-based logging system, improving debugging efficiency and dev
productivity by 25%.
– Engineered and deployed the Claim Intimation module with 99% UAT success rate and 99.9% system uptime, supporting
10,000+ test policyholders during claim processing.
– Built and integrated the Party Master module, cutting third-party onboarding time by 50% and enabling seamless
connectivity for 1,000+ insurance brokers.
– Developed RESTful APIs, optimized SQL stored procedures, and managed on-premise deployments, resulting in a 25%
increase in development throughput.
Asico (UAE)
– Delivered a robust preauthorization module, cutting authorization overhead by 40% and accelerating workflow efficiency
by 1.5× through streamlined request handling.
– Revamped complex legacy backend logic, boosting system performance by 20% by introducing query indexing and
eliminating redundant cursors.
Hrms Assuretech
– Enhanced the legacy Travel Claim module within the HRMS platform by optimizing database queries, resulting in a 45%
increase in document generation speed and a 95% reduction in failure rates
Sol-Yield, Trivandrum April 2023 – August 2023
Machine Learning Engineer(Intern)
Computer Vision Project — Internal Tool
– Constructed a mobile-compatible computer vision pipeline to validate solar system installations using YOLOv8 and
MiDaS, reducing manual inspection time by over 80%.
– Curated and labeled a proprietary dataset of 1,200+ field images captured by technicians across multiple installation
sites, covering inverter, BMS, breakers, and isolator placements.
– Trained a custom YOLOv8 model with targeted data augmentation (rotation, brightness, distortion) to generalize across
real-world variations in lighting and mounting.
– Integrated MiDaS depth estimation (DPT-Hybrid) to assess wall clearance, mounting height, and component spacing,
enabling spatial rule enforcement for safety verification.
– Released the pipeline to Android devices using ONNX and TensorFlow Lite, enabling offline inference and real-time
validation at remote installation sites
Projects & Achievements
CDD (Cardamom Disease Detection) April 2022 – April 2023
– Led the development of a custom dataset in collaboration with ICRI (Indian Cardamom Research Institute), collecting
over 65 days of field images across three disease categories: healthy, leaf blight, and leaf spot.
– Designed and trained a deep learning model using EfficientNetB1, achieving 88.31% accuracy via extensive
experimentation with Adam, SGD, and RMSprop optimizers.
– Implemented state-of-the-art practices in data preprocessing (normalization, augmentation, and stratified splitting),
improving generalization and robustness of the classifier.
– Evaluated EfficientNet and custom ResNet9 architectures, benchmarking performance for future deployment in UAV or
rover-based ONNX systems for precision agriculture.
– Prototyped a webcam-based prediction system to validate model performance in semi-real-time scenarios, demonstrating
practical usability for field deployments
Homie-Spot March 2023 – July 2023
– Launched a scalable B2B platform to standardize hostel and PG infrastructure, securing a state-level grant of INR 75,000
under the Kerala Government’s Young Innovators Program (YIP 4.0)
– Orchestrated a shared resource ecosystem for food, laundry, and waste services, cutting operational costs for multiple
providers within the same locality
– Devised a mobile/web portal enabling provider registration and infrastructure benchmarking aligned with UN living
standards
– Conceptualized a centralized “Hub” model for nutritious food prep, waste segregation, and service logistics, elevating
overall hygiene and service quality
W-Be-safe , Manage-it April 2021 – April 2021
– Secured a grant of INR 5,000 in a project presentation organized by CET for developing W-Be-safe, a women’s safety
mobile application
– Clinched the INR 1,00,000 first prize in a CET-hosted hackathon for building Manage-it, a money management app
focused on financial literacy and budgeting
Education
Government Engineering College, Idukki August 2019 – July 2023
Bachelor of Technology in Computer Science & Engineering Percentage: 74.2%
Coursework:
– DSA, OS, DBMS, OOP (Java), Microprocessors and Embedded Systems, Theory of Computation (TOC)
– Compiler Design, AI/ML, Discrete Mathematics, Probability & Statistics, Linear Algebra
