Hire the Best Computer Vision Engineers
in Ukraine

Design and deploy AI pipelines that transform image, video, and audio data into reliable real-world applications, from computer vision analytics and 3D perception to audio (speech, music, sound) analysis and generative AI systems. My work focuses on production AI systems, not research prototypes. I help companies move from early feasibility studies and PoC development to scalable deployments running in real environments. Typical projects include: • computer vision pipelines for detection, tracking, and segmentation • real-time video analytics and edge AI deployments • 3D vision and spatial perception systems • speech processing and audio AI solutions • generative AI pipelines for image, video, and audio Computer Vision Systems Design and development of advanced computer vision pipelines for image and video analysis. Typical solutions include: • object detection and multi-object tracking • semantic and instance segmentation • pose estimation and motion analysis • OCR and document understanding • visual search and recognition systems These systems are used in industries such as manufacturing, sports analytics, retail, healthcare, and security. 3D Vision & Spatial AI Development of AI systems that understand spatial structure and depth. Experience includes: • structure-from-motion (SfM) • photogrammetry pipelines • depth estimation models • NeRF and neural rendering • point cloud processing and 3D reconstruction Applications include robotics, AR/VR, construction analytics, and digital twins. Edge AI & On-Device ML I specialize in deploying ML models on mobile and embedded devices where latency, memory, and power constraints are critical. Typical optimization techniques include: • model quantization and pruning • architecture optimization • real-time inference pipelines • deployment on mobile and embedded hardware Technologies include: TensorRT, TensorFlow Lite, CoreML, ONNX Runtime. Many deployed systems operate with 50–100 ms inference latency depending on hardware. Generative AI for Vision & Video Development of generative pipelines for media processing and synthetic data generation. Typical solutions include: • image and video generation pipelines • diffusion-based editing and enhancement • synthetic dataset generation for model training These tools help accelerate AI training and improve model robustness. Audio & Speech AI Development of AI systems for speech processing, audio analysis, and voice technologies. Examples include: • phoneme segmentation and pronunciation analysis • speech recognition pipelines • voice feature extraction and audio analytics • generative audio and music models These systems are used in: • language learning platforms • speech therapy tools • voice biometrics systems • music AI applications Technical Stack Frameworks & Models PyTorch, TensorFlow, OpenCV, Detectron2, MediaPipe, YOLO, DINO, SAM, CLIP Deployment TensorRT, TensorFlow Lite, CoreML, Docker, ONNX Runtime, FastAPI Programming Python, C, C++ 3D Vision NeRF, SLAM, Dust3r, point clouds Leadership & R&D I lead an R&D-focused AI team at It-Jim, an AI consulting company with 30+ engineers and 10+ PhDs specializing in: • Computer Vision • Generative AI • Audio & Speech AI • Edge AI systems We help companies solve technically challenging AI problems and build reliable production systems. If you are looking for experienced AI engineers to design, prototype, or deploy advanced machine learning solutions: feel free to reach out!

𝐄𝐱𝐩𝐞𝐫𝐭-𝐕𝐞𝐭𝐭𝐞𝐝 𝐓𝐨𝐩 𝟏% 𝐨𝐧 𝐔𝐩𝐰𝐨𝐫𝐤 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 & 𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗩𝗶𝘀𝗶𝗼𝗻 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 I am an AI/ML Engineer with extensive experience in Machine Learning, Deep Learning, and Computer Vision, applying these technologies to real-world problems in diverse industries. My work focuses on the full lifecycle of Machine Learning solutions, from data acquisition and preprocessing to model training, evaluation, optimization, and deployment. I have over 15 years in software development and more than 7 years delivering production-grade Artificial Intelligence systems, with core expertise in Python, TensorFlow, OpenCV, Keras, and image processing. My specialization in Computer Vision covers image classification, object detection, object tracking, image segmentation, and pose estimation. I have delivered Computer Vision solutions for sports analytics, satellite imagery analysis, automated parking systems, industrial inspection, and security surveillance. I use OpenCV, TensorFlow, and Keras extensively to build robust image processing pipelines, integrating preprocessing, feature extraction, and model inference. By combining Deep Learning and Deep Neural Network Scripting with traditional image processing techniques, I ensure scalable and reliable outcomes. In Machine Learning, I design and implement algorithms for predictive analytics, time-series forecasting, anomaly detection, and digital signal processing. I have built models for structured and unstructured data, leveraging Python-based libraries to create reproducible, maintainable workflows. My expertise spans supervised, unsupervised, and reinforcement learning, with model performance tuned through hyperparameter optimization and cross-validation. I apply industry-standard evaluation metrics to ensure model accuracy and stability in production environments. My AI portfolio also includes projects in Natural Language Processing, ranging from sentiment analysis and text classification to entity recognition and contextual embeddings. These solutions have been deployed in customer support automation, content moderation, and document intelligence systems, integrating language models with domain-specific data for maximum accuracy. My Computer Vision work often integrates Convolutional Neural Networks (CNNs) and other neural architectures implemented in TensorFlow, Keras, and PyTorch. I develop custom CNNs for specialized vision tasks and deploy them into production systems with GPU acceleration. I have experience building multi-stage pipelines combining OpenCV for preprocessing with Deep Learning inference models for real-time video analysis. My solutions have included multi-camera tracking, 3D pose reconstruction, and visual quality control systems. In image processing, I work with still images and video streams, applying transformations, filtering, feature detection, and geometric corrections. I optimize pipelines using tools such as FFmpeg and MoviePy, enabling efficient processing at scale. My background includes developing algorithms for illumination correction, background subtraction, and high-speed video frame analysis. My Artificial Intelligence projects integrate Machine Learning and Computer Vision into broader systems. These include AI-powered web applications, embedded systems for edge AI, and cloud-based analytics platforms. I have built REST APIs using Python frameworks for serving AI models, integrating them with frontend applications in JavaScript and with third-party systems via secure endpoints. I implement MLOps practices, including containerized deployments with Docker, CI/CD pipelines, and model monitoring. I maintain strong expertise in data science and statistical analysis. I work with large datasets, ensuring correct data labeling, cleaning, and augmentation. I apply mathematical foundations to design efficient Machine Learning architectures. My workflow includes using Python’s scientific stack (NumPy, pandas, SciPy, scikit-learn) alongside TensorFlow, Keras, and OpenCV to create cohesive solutions. I focus on efficient data processing, AI model lifecycle management, and scalable software architecture. I design systems that optimize computational resources, use parallel processing for performance gains, and support integration with renewable energy-aware compute platforms when required. My solutions incorporate automation for data workflows, reducing manual intervention and ensuring sustainable, repeatable processes. If you are seeking an AI/ML specialist with proven experience in Machine Learning, Deep Learning, Computer Vision, Natural Language Processing, image processing, and Deep Neural Network Scripting in Python-based development, I can deliver solutions that meet performance, scalability, and maintainability requirements.

I hold an M.S. in Computer Science from Karazin National University, with a strong foundation in mathematical analysis and linear algebra, which I apply effectively to solve complex challenges in Machine Learning and Computer Vision. With 6 years of extensive commercial experience, I am an AI Engineer with a proven track record of leading development efforts and contributing to all stages of the product lifecycle, aligning technical advancements with business objectives. My expertise covers all major areas of Computer Vision, including image classification, object detection and tracking, image segmentation, and pose estimation. I have delivered impactful, end-to-end solutions in various fields, such as: - Video-driven Sports Game Action Analysis - Satellite Image Processing - AI-powered Smart Parking Systems - Real-time Video Surveillance Systems I specialize in developing custom neural network architectures for Computer Vision applications, leveraging frameworks like TensorFlow, Keras, and PyTorch, as well as tools like OpenCV, MoviePy, and FFmpeg for efficient image and video processing. My programming expertise spans Python and C++, and I have experience building CV-powered web applications using JavaScript. I have successfully contributed to projects in areas such as Sports Analytics, Parking Surveillance Systems, Satellite Image Processing, and Manufacturing & Analytics for the Beauty and Healthcare industries. Proficient in image classification, object detection, action recognition, and more, I leverage advanced neural networks to deliver effective solutions. In addition to my technical skills, I possess a strong foundation in Discrete Mathematics, Statistics, and Differential Equations, with specialized knowledge in digital signal processing, time-series analysis, and unsupervised learning. While working effectively in team environments, I also understand the importance of business logic and strategic goals. I’ve helped businesses and enterprises achieve their goals, drive financial growth, and automate processes to generate significant gains.

I build production-ready Machine Learning and AI-powered mobile systems focused on real-time performance, on-device inference, and computer vision integration. My work sits at the intersection of: • Machine Learning engineering • AI Mobile App Development (iOS-focused) • Edge AI & on-device ML optimization • Computer Vision (2D & 3D pipelines) • Spatial & AR-based AI systems I specialize in bringing ML models out of research and into real-world applications — where latency, model size, and hardware constraints actually matter. What I Deliver ✔ Integration of ML models into mobile applications (CoreML, TensorFlow Lite, ONNX) ✔ Real-time computer vision pipelines (detection, tracking, segmentation, 3D reconstruction) ✔ Edge AI system architecture ✔ AI-powered AR applications ✔ Model optimization for mobile GPUs and hardware accelerators ✔ ML MVP and Proof-of-Concept development ✔ Deployment-ready AI systems Applied Experience • AI-powered sports analytics systems • 3D scanning & reconstruction using mobile sensors • AR-based interaction systems with embedded ML • AI-driven mobile health and measurement solutions • Spatial AI and real-time camera processing If you need an ML engineer who understands both model behavior and production deployment on mobile/edge devices — let’s talk.

✩░▒▓▁𝐒𝐫. 𝐀𝐈/𝐌𝐋 & 𝐂𝐕 | 𝐀𝐈 𝐅𝐮𝐥𝐥-𝐒𝐭𝐚𝐜𝐤 | 𝐑𝐞𝐚𝐜𝐭/𝐍𝐨𝐝𝐞/𝐏𝐲𝐭𝐡𝐨𝐧, 𝐎𝐂𝐑, 𝐘𝐎𝐋𝐎/𝐓𝐞𝐧𝐬𝐨𝐫𝐅𝐥𝐨𝐰▁▓▒░✩ I am a Senior AI/ML & Computer Vision Engineer with 8+ years of experience building production-ready AI systems. I specialize in computer vision, OCR, and deep learning using YOLO and TensorFlow, and deliver end-to-end solutions with Python, Node.js, and React. My focus is on high-performance, scalable AI deployed in real-world applications. ⚡ Core Expertise in Real-Time Computer Vision • Object Detection & Tracking: YOLOv8–YOLOv10, DeepSORT, ByteTrack, SORT • Real-Time Video Analytics: CCTV analytics, intrusion detection, object counting, anomaly detection • RTSP & Live Streams: Multi-camera RTSP pipelines, IP cameras, CCTV, drones • OCR & Video Text Extraction: License plate recognition, IDs, invoices, on-video OCR • Edge & Low-Latency AI: NVIDIA GPU, Jetson, edge inference optimization • Camera-Based Monitoring: PPE detection, safety compliance, zone-based alerts ⚡ AI Models & Computer Vision Techniques • Object detection, tracking, and re-identification • Motion analysis and behavior detection • Computer vision–based automation workflows • Real-time inference optimization • Image preprocessing and video frame handling ⚡ Tools, Frameworks & Platforms • Frameworks: PyTorch, TensorFlow, Ultralytics YOLO • CV Libraries: OpenCV, FFmpeg, GStreamer • Tracking: DeepSORT, ByteTrack • APIs & Services: FastAPI, Flask • Deployment: Docker, NVIDIA GPUs, Jetson, AWS EC2 • Languages: Python, C++, JavaScript ⚡ Mobile & Full-Stack Integration • Mobile app development using Flutter and React Native • Live camera viewing and RTSP stream playback on mobile • Real-time AI alerts and notifications • Backend APIs for video metadata and detection results • Dashboards for monitoring AI events and analytics 🏆 Featured Projects • Real-Time CCTV Object Detection: Built a YOLO-based system for restricted-zone monitoring and intrusion alerts via RTSP. • ANPR / License Plate Recognition: Implemented real-time OCR for traffic automation and parking management. • Multi-Camera Analytics Platform: Created a scalable pipeline to process dozens of simultaneous RTSP streams with event logging. • PPE & Safety Monitoring: Automated detection of helmets and safety gear for industrial compliance. • Mobile Camera Monitoring App: Developed a custom mobile solution for live AI-event viewing and instant notifications. • Hand-Touch Detection Model: Optimized a high-speed model for edge AI applications. ⚙️ How I Work 1. Production-First Mindset: I build systems meant to run 24/7, not just research demos. 2. Performance Focused: I optimize every frame for the best balance of accuracy and FPS. 3. End-to-End Delivery: I handle the entire lifecycle: Model → API → Mobile App → Deployment. 4. Transparent Communication: Clear documentation, fast iterations, and long-term support. If you need an engineer to turn your camera feeds into a powerful AI asset, click the "Message" or "Invite" button. I’m ready to audit your setup and provide a technical roadmap. Best Regards, Oleksandr T. ### Skills ### To maximize your visibility in Upwork’s search algorithm and ensure you cover every technical niche mentioned in your profile, here are 100 important skillsets formatted as requested: " Computer Vision, Artificial Intelligence, Machine Learning, Deep Learning, Image Processing, Video Analytics, Real-Time Stream Processing, RTSP, CCTV, IP Cameras, YOLOv8, YOLOv9, YOLOv10, YOLOv11, Object Detection, Object Tracking, Multi-Object Tracking (MOT), Facial Recognition, OCR, License Plate Recognition (ANPR), Python, C++, OpenCV, PyTorch, TensorFlow, Keras, Ultralytics, MediaPipe, FFmpeg, GStreamer, NVIDIA Jetson, NVIDIA Jetson Nano, NVIDIA Xavier, NVIDIA Orin, Edge AI, Edge Computing, GPU Acceleration, CUDA, TensorRT, Model Optimization, Model Quantization, Model Pruning, ONNX, Docker, Containerization, FastAPI, Flask, REST API, Backend Development, Full-Stack Development, Flutter, React Native, Mobile App Development, iOS Development, Android Development, Live Video Streaming, Video Latency Optimization, Pose Estimation, Behavior Analysis, Anomaly Detection, Intrusion Detection, People Counting, Crowd Analysis, Traffic Monitoring, PPE Detection, Safety Compliance, Industrial Automation, Retail Analytics, Drone Vision, Action Recognition, Motion Detection, Image Segmentation, Semantic Segmentation, Instance Segmentation, DeepSORT, ByteTrack, SORT, Kalman Filter, Image Preprocessing, Video Manipulation, AWS EC2, AWS Panorama, Cloud AI, On-Premise AI Deployment, Linux, Ubuntu, Shell Scripting, Git, Version Control, CI/CD for AI, Scalable AI Pipelines, Technical Documentation, System Architecture, Algorithm Development, Data Augmentation, Dataset Labeling, AI Model Train

Hi! I'm a software developer focusing on computer vision, image processing, and back-end development. I have hands-on experience taking ML projects from a proof-of-concept to the production stage. I worked on image generation workflows where I helped reduce inference time by 44% using TensorRT. I also built a full-stack computer vision platform that hosts over 20 ML models for tasks like object detection, segmentation, and captioning via REST API. On the back-end side, I'm comfortable setting up REST APIs with FastAPI and C#, configuring Ubuntu servers and Nginx, and handling databases. I've also done short-term consulting for image generation models like Stable Diffusion and FLUX, and I have experience contributing to UAV development and 3D printing in my free time. Tech Skills: Python, C#, JavaScript, React. PostgreSQL, MongoDB, SQL Server. FastAPI, ASP.NET, Nginx. PyTorch, Tensorflow, Scikit-learn, Pandas, Numpy. Image processing, Data augmentations, ML Model Tracking/Logging. Diffusion models, Unet, SAM, Yolo, ResNet, LLM, Stable Diffusion, FLUX. VPS, AWS, EC2, S3, CI/CD. Linux, Ubuntu Server, Bash, Docker, SMTP.