Hire the Best TensorFlow Developers

WebRTC, FFmpeg, AI, OpenCV, Streamin – I fix real-time video apps and have since 2005. 13,485 hours, 14 projects, 100% Job Success. Zero abandoned. ⚡ 𝗙𝗿𝗲𝗲 𝗣𝗥𝗗. 𝗠𝗩𝗣 𝗶𝗻 𝟳-𝟭𝟰 𝗱𝗮𝘆𝘀. 𝗙𝗿𝗲𝗲 𝗰𝗼𝗱𝗲 𝗿𝗲𝘃𝗶𝗲𝘄 𝗼𝗿 𝟮-𝘄𝗲𝗲𝗸 𝘁𝗿𝗶𝗮𝗹 𝗼𝗻 𝗮𝗻 𝗲𝘅𝗶𝘀𝘁𝗶𝗻𝗴 𝗰𝗼𝗱𝗲𝗯𝗮𝘀𝗲. Netflix, HBO, EA, Nokia, the World Bank, and Harvard trust platforms I've built. These clients don't give second chances. Mine work. ⚠️ Invite me to your job – I reply within 15 minutes. 𝗦𝗲𝗹𝗲𝗰𝘁𝗲𝗱 𝗢𝘂𝘁𝗰𝗼𝗺𝗲𝘀 → Speed.Space – live production platform for Netflix, HBO, EA, and Apex Legends. Multi-stream switching, real-time collaboration, pro codec control. Used at Paris Fashion Week and Live Nation events. Zero downtime. → ShortKlips – video project management for Nokia and the World Bank. 200K+ monthly video views. Cut client project turnaround by 30%. → VirtualCr8tive – hybrid event platform for Harvard University and U.S. Vets. → CloudDoctors – HIPAA-compliant telehealth on WebRTC. Built from concept through multiple release cycles. → YUUALL – WebRTC platform built across multiple versions, long-term engagement. 𝗪𝗵𝗲𝗿𝗲 𝗜'𝗺 𝗦𝘁𝗿𝗼𝗻𝗴𝗲𝘀𝘁 – Pipeline latency – I profile FFmpeg filter graphs and cut processing time without losing quality. – WebRTC under load – jitter buffer, codec mismatch, TURN/STUN. I find which one is yours fast. – AI on live video – TensorFlow inference under 80ms; object and audio recognition on live feeds. – FFmpeg deep work – custom filter graphs, muxing, hardware acceleration (NVENC, VAAPI, VideoToolbox). – Scale & reliability – systems handling 600M+ call minutes a month, fixed at the architecture level. 𝗦𝗽𝗲𝗰-𝗙𝗶𝗿𝘀𝘁 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 I work spec-first, not vibe-first. I write the full spec and architecture before any code. Then I drive AI agents: developer, tester, analyst – against strict guardrails to produce production-grade code. The hard real-time work I handle or verify myself: WebRTC pipelines, sub-second latency, on-device ML. You get AI speed with the stability of a senior engineer, 4-10× faster than classic coding. 𝗛𝗼𝘄 𝗜 𝗪𝗼𝗿𝗸 You describe what's broken or what you're building. I send back a diagnosis: the problem, the fix, the cost. Not a sales call. Then we scope the work together before either of us commits. My estimates average ~10% off actuals. I validate before building and run staged QA on every release. 𝗛𝗼𝘄 𝗬𝗼𝘂 𝗖𝗮𝗻 𝗪𝗼𝗿𝗸 𝗪𝗶𝘁𝗵 𝗠𝗲 1. Build from scratch – real-time video, AI, or streaming, end-to-end. 2. Drop in on your team – I take the hard video, AI, or WebRTC modules. 3. Rescue and modernize – fix slow or unstable platforms and ship to production. I work inside the Fora Soft team – 51-200 engineers. If your project grows, a PM, QA, and more developers are already there. No solo freelancer who vanishes when scope expands. 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝗶𝗲𝘀 𝗜 𝗨𝘀𝗲 𝗗𝗮𝗶𝗹𝘆 ◆ Real-time & video: WebRTC, LiveKit, FFmpeg, GStreamer, OpenCV, HLS/DASH, RTMP/RTSP, OBS, WebGL ◆ AI & ML: TensorFlow, PyTorch, OpenAI API, Whisper, YOLO, object and audio recognition ◆ Back-end: Node.js, Python, TypeScript, distributed systems, high-load APIs ◆ Cloud & infra: AWS, GCP, Docker, Kubernetes, CI/CD 𝗪𝗵𝘆 𝗙𝗼𝗿𝗮 𝗦𝗼𝗳𝘁 The team behind me: 914 jobs · $10M+ earned · 401K+ hours · 250+ projects since 2005 · 400+ clients across 17+ countries · Top WebRTC & Telecom Developer 2022 and 2024 · 1 of 400 devs passes our internal selection. 𝗖𝗹𝗶𝗲𝗻𝘁 𝗙𝗲𝗲𝗱𝗯𝗮𝗰𝗸 "We enjoyed working with Andrey. He saw himself as part of our team and proactively contributed. Even last-minute requests were handled in a timely, constructive way. Many of his proposals were better than our own ideas." – client, YUUALL (WebRTC platform) ⚠️ Describe what's broken. I'll tell you what's wrong, how to fix it, and what it costs.

I build production-ready computer vision systems, backed by 4+ years of hands-on experience — real-time detection, segmentation, and tracking that run fast and stay stable on NVIDIA Jetson, GPU workstations, on-prem servers, and in the cloud. It starts with data. I specialize in high-precision video and image annotation, but I don't stop at labeling: I build clean, consistent datasets and use them to train high-performing YOLO and custom CNN models, so you get an end-to-end solution rather than just a labeled folder. From dataset creation to YOLO training, TensorRT optimization, and production integration — including live CCTV stream inference — I build computer vision systems that work reliably on real hardware. WHAT I DELIVER - Dataset Creation & Annotation High-precision bounding-box, polygon, and video annotation; dataset cleaning, class balancing, and consistency checks - End-to-End Deep Learning Pipelines Data collection & annotation → dataset optimization → model architecture selection → training → evaluation → optimization → deployment - Real-Time Object Detection & Multi-Object Tracking Optimized YOLO pipelines with stable tracking (DeepSORT / ByteTrack / BoT-SORT / McByte) - Real-Time CCTV Stream Inference Multi-camera RTSP/IP stream processing, live detection and tracking, and event-based alerts on edge or server hardware - OCR & Document Intelligence OCR model training and optimization (PaddleOCR, Tesseract, EasyOCR), document preprocessing, information extraction, structured output, and handling of difficult documents (low quality, skewed, handwritten, multi-language) - Edge AI Acceleration & Performance Optimization TensorRT conversion, CUDA acceleration, latency reduction, memory tuning, FPS improvements TECH STACK Deep Learning: PyTorch, CNN architectures, YOLO variants Computer Vision: OpenCV, real-time video processing, detection & tracking, CCTV/RTSP streams OCR: PaddleOCR, Tesseract, EasyOCR Optimization: TensorRT, CUDA Systems: Linux, embedded systems, NVIDIA Jetson Annotation Tools: CVAT, Roboflow, LabelMe, MakeSense.ai, and others Share your goal and a sample of your data, and I'll propose a clear technical approach and a realistic delivery plan.

For more than 10 years I have managed iOS app development. I was also responsible for defining architecture. I have hands on with development of iOS apps in Swift, SwiftUI and Objective-C. I also have hands-on knowledge of Flutter App development. I have developed Flutter app for Vehicle Tracking, Object Detection and Image Segmentation (SSD MobileNet, YOLO, DeepLab+MobileNet) using TensorFlow Lite. I am also PSM I certified. I can provide services as a SCRUM master.

I am an AI/ML developer specializing in Computer Vision, Embedded AI, and real-world automation systems. I work with startups, researchers, and small businesses to design and deploy practical machine learning models that solve real operational problems. With a Bachelor's degree in Computer Engineering (Nanotechnology option) from the University of Alberta, I have hands-on experience with: 1) Object Detection and Face Recognition using OpenCV and YOLO 2) Embedded AI solutions using TensorFlow Lite on Raspberry Pi and Arduino 3) GPT/LLM integration for custom chatbot and PDF summarization tools 4) Automation pipelines using Python, Pandas, Scikit-learn, and Flask 5) Dashboard development with Streamlit and model deployment via APIs I focus on clear code, real results, and business-driven AI—not just academic models. Whether you need help with a one-time project or a long-term collaboration, I deliver production-ready, well-documented solutions with a strong understanding of both software and hardware aspects. Let’s connect if you’re looking for an AI partner who understands systems from edge devices to APIs.