Senior Computer Vision Engineer - Real-time Edge AI (OpenCV, ONNX, CUDA & TensorRT)

@MashoodurRehman1

I am a Senior Computer Vision Engineer with extensive experience in developing real-time Edge AI systems. My proficiency in Python 3.10+ with an OOP architecture aligns well with your project requirements. I have a proven track record of leveraging advanced OpenCV for high-precision OCR and object detection, along with expertise in using inference engines like ONNX Runtime, OpenVINO, and TensorRT with CUDA. My skills in implementing multi-threading and circular buffers ensure optimal video ingestion and processing efficiency. In my previous projects, I have successfully implemented batch processing on GPU to handle multiple ROIs simultaneously, achieving low-latency outcomes similar to your objectives. I have designed State Trackers for generating Sequence Keys from visual action histories and developed Confidence Buffers to improve accuracy by reducing false positives. Using PyQt6, I can create overlays that maintain system performance seamlessly. I am keen to discuss how I can contribute to your project and am ready to provide a latency proof of concept. Can you share more details about the expected input sources? Best regards.

@ZohaibRoy

⭐⭐⭐⭐⭐ Senior Computer Vision Engineer for Real-time Edge AI Solutions ❇️ Hi My Friend, I hope you're doing well. I've reviewed your project requirements and see you are looking for a Senior Computer Vision Engineer. You have no need to look any further; Zohaib is here to help you! My team has successfully completed 50+ similar projects in Edge AI. I will create a system that processes HDMI video, performs high-accuracy OCR, and detects objects with low latency. I will use Python, OpenCV, and TensorRT to ensure efficiency within your budget. ➡️ Why Me? I can easily do your project as I have 5 years of experience in computer vision and Edge AI. My expertise includes Python programming, OpenCV, and real-time image processing. Additionally, I have a strong grip on ONNX, TensorRT, and multi-threading techniques. ➡️ Let's have a quick chat to discuss your project in detail. I can show you samples of my previous work. Looking forward to our chat! ➡️ Skills & Experience: ✅ Python 3.10+ ✅ OpenCV ✅ ONNX Runtime ✅ TensorRT ✅ CUDA ✅ Image Processing ✅ Multi-threading ✅ OCR Implementation ✅ Batch Processing ✅ PyQt6 ✅ Database Querying ✅ System Optimization Waiting for your response! Best Regards, Zohaib

@hoangnn90

✅Full Experience in Image Processing and Computer Vision with Python Programming(OpenCV)✅. ✳️I am very confident that complete your project perfectly. ✳️I can guarantee the quality of the job and deliver the result on time. I hope we will discuss in more detail via chat. Best regards!

@quan9824

I am a Senior Computer Vision Engineer specializing in real-time Edge AI with proven experience delivering sub-100ms latency systems on resource-constrained hardware. I have worked extensively with OpenCV, ONNX Runtime, TensorRT/CUDA, and OpenVINO for hardware-aware optimization across NVIDIA and Intel platforms. I have built pipelines that ingest HDMI/RTSP video, run OCR and multi-object detection, and query local databases while maintaining strict latency budgets. My approach focuses on zero-copy memory management, asynchronous GPU execution, and ROI-based batch inference to maximize throughput. Technically, I will: • Design an OOP modular architecture with abstract interfaces • Implement multi-threaded video ingestion with circular buffers • Optimize batch GPU processing for 8+ ROIs per cycle • Develop high-accuracy OCR for stacks/bottles using custom preprocessing • Build a reliable confidence buffer and state-machine sequence tracker • Create a lightweight PyQt6 transparent overlay without FPS impact I am comfortable delivering a latency PoC as the first milestone and working hands-on with profiling tools (Nsight, perf, OpenVINO benchmark tools) to validate results. I am not a generalist web developer; my background is low-latency visual inference, real-time systems, and hardware optimization. Ready to start immediately and discuss technical details.

@abhisaini0188

Hello, Thank you so much for posting this opportunity. It sounds like a great fit, and I’d love to be part of it! I’ve worked on similar projects before, and I’m confident I can bring real value to your team. I’m passionate about what I do and always aim to deliver work that’s not only high-quality but also makes things easier and smoother for my clients. Feel free to take a quick look at my profile to see some of the work I’ve done in the past. If it feels like a good match, I’d be happy to chat further about your project and how I can help bring it to life. I’m available to get started right away and will give this project my full attention from day one. Let’s connect and see how we can make this a success together! Looking forward to hearing from you soon. With Regards! Abhishek Saini

@efanntyo

Hello Xabier Adrian G. Thanks for posting this exciting project, I am really interested in your project. Because I am working on 7 years over with Python, CUDA, Machine Learning (ML), OCR, Image Processing, OpenCV, Video Processing, Computer Vision, Deep Learning, I can provide good result in your needed timeline. I am looking forward to discussing more with you soon. Regards Efanntyo -.

@Ahmedh058

Hi there, I’m Ahmed from Eastvale, California — a Senior Full-Stack Engineer with over 15 years of experience building high-quality web and mobile applications. After reviewing your job posting, I’m confident that my background and skill set make me an excellent fit for your project. I’ve successfully completed similar projects in the past, so you can expect reliable communication, clean and scalable code, and results delivered on time. I’m ready to get started right away and would love the opportunity to bring your vision to life. Looking forward to working with you. Best regards, Ahmed Hassan

@GameOfWords

Senior Computer Vision Engineer - Real-time Edge AI (OpenCV, ONNX, CUDA & TensorRT) I’m a full-stack software engineer with expertise in React, Node.js, Python, and cloud architectures, delivering scalable web and mobile applications that are secure, performant, and visually refined. I also specialize in AI integrations, chatbots, and workflow automations using OpenAI, LangChain, Pinecone, n8n, and Zapier, helping businesses build intelligent, future-ready solutions. I focus on creating clean, maintainable code that bridges backend logic with elegant frontend experiences. I’d love to help bring your project to life with a solution that works beautifully and thinks smartly. To review my samples and achievements, please visit:https://www.freelancer.com/u/GameOfWords Let’s bring your vision to life—connect with me today, and I’ll deliver a solution that works flawlessly and exceeds expectations.

@vinod00k

Hello ,I reviewed your project requirements and I’m confident that my technical expertise aligns well with what you’re looking for. I specialize in designing and developing scalable applications with a focus on performance, clean architecture, and long-term maintainability. My Technical Expertise Includes: AI & Automation — NLP, predictive analytics, chatbot development, workflow automation Python Development — FastAPI / Flask / Django, API development, backend architecture MERN Stack — MongoDB, Express, React, Node.js for full-stack web applications Mobile Development — React Native & Flutter for high-performance cross-platform apps Cloud & Integrations — Firebase, AWS, REST APIs, micro-services architecture I believe in clear communication, timely delivery, and building solutions that are not just functional — but future-ready, scalable, and optimised for real-world use. Whether the requirement is a small module or a full-scale system, I’m confident that I can deliver with precision, quality, and reliability. I would be glad to discuss your technical scope further and collaborate with you to bring your project to life. Looking forward to connecting with you. Best regards,


@sekai1116

✅ Nice to meet you here ✅ I’m an experienced computer vision engineer specializing in real-time Edge AI with Python, OpenCV, ONNX, TensorRT, and CUDA. I can build your low-latency HDMI video processing system with high-accuracy OCR and object detection, including multi-threaded pipelines, batch ROI processing, and PyQt6 overlays. I can deliver a proof-of-concept demonstrating <100ms latency and implement the State Tracker and Confidence Buffer for robust real-time performance. Looking forward to contributing my expertise to your project. Best regards, Jiayin

@abanoubnashaat99

Hola, with solid experience in real-time computer vision and Edge AI, I can build a low-latency HDMI video processing pipeline with OCR and object detection, optimized for sub-100 ms end-to-end performance. The focus would be efficient buffering, batch GPU inference, and hardware-specific optimization using ONNX Runtime, OpenVINO, or TensorRT. Happy to align on the PoC scope and get straight to work.

@dataspro

Un gusto hablarte , Es un placer comunicarme con usted. Mi nombre es Anthony Muñoz, soy el ingeniero líder de la agencia de TI DSPro y me gustaría ofrecerle mis servicios profesionales. Tengo más de 10 años de trabajo como desarrollador de Backend y Software, he realizado con éxito numerosos trabajos similares al tuyo por lo tanto, y después de leer detenidamente los requisitos de tu proyecto, considero que este trabajo es adecuado para mi área de conocimiento y habilidades. Me encantaría trabajar juntos para hacer realidad este proyecto. Agradezco mucho el tiempo brindado y quedo pendiente para cualquier duda o comentario. No dude en ponerse en contacto conmigo. Saludos

@oleksandrf3

I NEVER USE AI FOR BIDDING! Necesitas procesamiento de video HDMI en tiempo real con OCR preciso, detección de objetos y latencia inferior a 100ms usando Edge AI optimizado. He desarrollado sistemas idénticos de visión artificial de baja latencia con OpenCV, OCR, ONNX Runtime, TensorRT y multi-threading para video en hardware dedicado. Looking forward to discussing more details. Lenguaje: Python OOP Visión: OpenCV avanzado, procesamiento de imagen Inferencia: ONNX Runtime, OpenVINO, TensorRT, CUDA Optimización: Batch GPU, procesamiento simultáneo de ROIs Arquitectura: Multi-threading, buffers circulares UI: PyQt6 overlays

@thomasb726

⭐If you award me, your smile shows up.⭐ Hi Your project really caught my attention — it’s very similar to one I completed recently. The setup feels familiar, with the same kind of challenges, just a few unique details. That’s actually great news, because it means I already know what works and can move fast without trial and error. Most importantly, I have deep experience and hands-on expertise with OpenCV, Image Processing, Deep Learning, OCR, Machine Learning (ML), Video Processing, Computer Vision, CUDA and Python. In my portfolio, you can find a project similar to yours. https://www.freelancer.com/u/thomasb726 If you’re open to it, I’d love to hear more about what you’re building and share a few ideas from my past experience. ❓ Why clients choose me: ✅ Clear, fast, and proactive communication — you’ll never be left guessing where things stand. ✅ I treat your deadlines and reputation like my own — because once we start, they are. ✅ Easy to talk to, quick to respond, and focused on making your job easier. ✅ I always stand by and support the clients I work with, even long after delivery. Many of my clients stay with me long-term — because I show up, deliver, and don’t disappear. If you’re looking for a project executed with precision and quality, let’s chat soon and get started. Best, Tom

@enocki8

Hola, Soy Senior Computer Vision Engineer con experiencia práctica en Edge AI de baja latencia y sistemas en tiempo real basados en vídeo, exactamente en el tipo de reto técnico que describes. He trabajado en pipelines end-to-end donde la latencia (<100 ms) y la optimización de hardware no son opcionales, sino requisitos de diseño. Mi experiencia relevante incluye: Python 3.10+ con arquitectura OOP escalable, uso de interfaces abstractas y separación clara de ingestión, inferencia y post-procesado. OpenCV avanzado para preprocesado, segmentación de ROIs y OCR de alta precisión en condiciones no ideales. ONNX Runtime, OpenVINO y TensorRT (CUDA) para despliegues optimizados tanto en Intel como en NVIDIA. Batch inference en GPU, procesando múltiples ROIs simultáneamente para maximizar throughput sin aumentar latencia. Arquitecturas multihilo con buffers circulares, desacoplando captura HDMI, inferencia y renderizado para evitar cuellos de botella. Diseño de state machines y trackers temporales para generar claves de secuencia basadas en historial visual. Implementación de confidence buffers y filtros temporales para reducir falsos positivos. Overlays ligeros con PyQt6, diseñados para no interferir con el pipeline de inferencia. Entiendo que este no es un proyecto web ni experimental, y estoy cómodo entregando una PoC con mediciones reales de latencia en el primer hito. Disponible para comenzar de inmediato. Saludos, Enock Isaboke

@anilptk

Hello there, I am thrilled to submit my proposal for the Senior Computer Vision Engineer position focusing on Real-time Edge AI utilizing OpenCV, ONNX, CUDA, and TensorRT technologies. I bring demonstrable expertise in developing a real-time tactical assistance system based on external video capture, with a primary technical challenge of processing HDMI video streams, high-precision OCR, object detection, and querying a local database within an end-to-end latency of less than 100ms. My key responsibilities would include designing a State Tracker to generate a Sequence Key... Regards, anilptk

@ivank69

Hey there What is the target edge hardware for the first milestone (Intel CPU with iGPU, NVIDIA Jetson, or desktop GPU), and which one defines the <100 ms latency requirement? For the OCR and object detection, are models already selected, or is part of the task to benchmark and choose models that meet latency under TensorRT / OpenVINO? This is a serious low-latency Edge AI system, and the requirements are very clear. The right approach is a modular Python architecture with strict separation between video ingest, inference, state tracking, and UI overlay, optimized end to end for hardware acceleration. A similar challenge was handled before where real-time video streams had to be processed with OCR and object detection under tight latency budgets. The main problem was not model accuracy, but pipeline bottlenecks caused by CPU-GPU sync, buffer contention, and inefficient ROI handling. This role fits very well with real-time computer vision, GPU optimization, and edge deployment. Ready to start immediately, deliver a latency-focused proof of concept in the first milestone, and iterate toward a production-grade system. Hope to discuss more on chat. Best, Ivan

@jovicaa

⭐ PyQt6 || OCR ⭐ I have read your job description carefully. I’m a Senior Computer Vision Engineer with strong experience in OpenCV, ONNX, CUDA, and TensorRT for real-time AI systems. I’ve worked on optimizing OCR and object detection for low-latency applications, using Batch Processing on GPU for simultaneous ROI processing. I’ll design the State Tracker, implement the Confidence Buffer, and create the PyQt6 overlay while maintaining system performance. I’m confident we can achieve the desired results. BEST REGARDS Jovica.

@kareemmaize

Hi, there. The hardest part here isn’t OCR accuracy, it’s deterministic latency under continuous video. I’ve seen edge systems pass benchmarks and still miss targets once multi-threading, buffering, and overlays run together. That usually happens when ingestion, inference, and post-processing share blocking paths. I mitigate this by isolating stages with circular buffers, pinning threads, batching ROIs on GPU, and validating timing at each boundary before adding features. I’d start by instrumenting the HDMI capture path, then lock a state tracker and confidence buffer, followed by ONNX/TensorRT optimization and OpenVINO tuning for Intel. The PyQt overlay comes last to avoid perturbing the pipeline. The first milestone is a latency-proven PoC, not a UI demo. Do you already have target hardware defined for both Intel and NVIDIA paths?