Hire the Best CUDA Developers

I am an AI/ML engineer with 3+ years building production machine-learning systems, backed by a research track record: two accepted peer-reviewed papers, a two-time Google Summer of Code contributor, and published GPU work. What I can build for you: • LLM & vision-language fine-tuning — QLoRA/PEFT, dataset creation, evaluation, deployment-ready inference. • Self-hosted & open-source LLM deployment — running models on your own GPU servers for privacy, control, and lower cost. • RAG systems & AI agents — retrieval grounded in your documents, data, and tools, with evaluation and monitoring so it stays reliable in production, not just in a demo. • GPU & scientific computing — CUDA/CuPy/JAX acceleration, profiling, and pipelines that process terabytes of data • Full-stack delivery — FastAPI backends, React/Electron front-ends, Docker/Kubernetes, so the model ships as a real product your team can run How I work: define the use case, build the smallest reliable version first, test the edge cases, document everything, and hand you code your team can maintain after the contract ends. Core stack: Python, PyTorch, Hugging Face, CUDA/CuPy, FastAPI, React, Docker, Kubernetes. I am Top Rated with 100% Job Success and I reply within a few hours. Tell me what you're trying to build and I will build it for you.

I design, optimize, and integrate real-time object detection and tracking pipelines for NVIDIA Jetson, RK3588, and cloud environments — with measurable gains in FPS, latency, and deployment stability. From YOLO training to TensorRT optimization and production integration, I build Computer Vision systems that work reliably on real hardware. If you need more than just a trained model — if you need a working AI system integrated into hardware or software — I deliver complete, production-ready solutions. 🎯 WHAT I DELIVER • End-to-End Deep Learning Pipelines Model architecture → dataset optimization → training → evaluation → deployment • Real-Time Object Detection & Multi-Object Tracking Optimized YOLO pipelines with stable tracking (DeepSORT / ByteTrack / BOT-SORT) • ⚡ Edge AI Acceleration & Performance Optimization TensorRT conversion, CUDA acceleration, latency reduction, memory tuning, FPS improvements • 🔗 AI Integration into Production Systems Jetson deployment, inference APIs, embedded integration, debugging, monitoring & system optimization 🏆 PROVEN EXPERIENCE • 5★ Upwork reviews for NVIDIA Jetson Nano, AGX & Orin deployments • Deployed Frigate and real-time CV pipelines on Jetson Orin NX • Optimized inference performance using TensorRT for improved real-time execution • Installed and configured LLM environments with secure key management & usage tracking • Research & production AI deployment experience at HBrain 🛠 TECH STACK Deep Learning: PyTorch, CNN architectures, YOLO variants Computer Vision: OpenCV, real-time video processing, detection & tracking Optimization: TensorRT, CUDA Systems: Linux, Embedded Systems, NVIDIA Jetson Languages: Python, C++ If you share your hardware target, dataset sample, or performance goal, I can propose a clear technical architecture and realistic delivery plan.

👋 Hi, I’m Mohamed — a Top Rated🏆 Senior Software Engineer. 🚀 I help companies design, build, and deliver high-performance software systems — from computer vision and AI pipelines to real-time desktop applications and embedded platforms. 🧩 What I deliver: ✅ Industrial Computer Vision Systems 🔹Integration with industrial cameras (Basler, Luxonis, FLIR / Point Grey) 🔹High-accuracy inspection, measurement, and defect detection 🔹Optimized OpenCV pipelines in C++ and Python 🔹Hybrid pipelines combining deep learning with classical computer vision for robustness ✅ Deep Learning (ResNet, U-Net, YOLO, MediaPipe, ...) 🔹Custom dataset creation, labeling, and curation 🔹Inference optimization for CPU, GPU, and edge devices 🔹YOLO for real-time object detection, segmentation, OBB, and pose estimation 🔹YOLO fine-tuning and transfer learning for domain-specific data 🔹MediaPipe for pose estimation, hand tracking, face landmarks, and motion analysis ✅ Real-Time & Performance-Critical Software 🔹Low-latency C++ systems optimized for speed and memory 🔹Multithreading, SIMD, profiling, and algorithmic optimization 🔹GPU acceleration (CUDA) when justified 🔹Designed for long-running, production-grade operation under real-world constraints ✅ Embedded & Edge AI 🔹Vision and AI deployment on Raspberry Pi 🔹Sensor integration, control logic, and hardware-in-the-loop testing with ESP32, Arduino ✅ Full Project Ownership 🔹System architecture and technical leadership 🔹Desktop GUIs: Qt, MFC, OpenGL 🔹Clean handover, documentation, and maintainable codebases 👉 Let's discuss how I can bring your AI, computer vision, or embedded system project to life.

I help startups and AI companies build high-performance AI systems, GPU-accelerated applications, and scalable AI infrastructure using CUDA, Rust, and Python. My expertise focuses on performance engineering, AI infrastructure, parallel computing, and low-latency systems designed for production-scale workloads. I work on optimizing compute-heavy applications, improving inference performance, and building reliable backend systems for modern AI products. I specialize in: • CUDA & GPU Optimization • AI Inference Optimization • Rust-based High Performance Systems • AI Infrastructure Engineering • Parallel Computing • Low-Latency Backend Systems • Python-based AI & Automation Systems • LLM Infrastructure • RAG Architecture & AI Search • Scalable API & System Architecture I can help with: ✅ GPU acceleration and CUDA optimization ✅ AI inference performance tuning ✅ Rust backend systems for high-performance workloads ✅ AI infrastructure and deployment pipelines ✅ Memory and compute optimization ✅ Parallel processing systems ✅ AI search and RAG pipelines ✅ Python automation and backend development ✅ Scalable distributed systems ✅ Production-ready AI architecture Tech Stack & Tools: CUDA, Rust, Python, PyTorch, TensorRT, ONNX, Docker, FastAPI, PostgreSQL, Vector Databases, REST APIs, WebSockets, AWS, Azure, and cloud-native architectures. I focus on building systems that are: * performant * scalable * efficient * reliable * production-ready If you are building GPU-intensive applications, AI infrastructure, inference systems, or performance-critical software, I’d be happy to discuss your project. Send me a message, and let’s discuss how we can make it happen!

🏆Top Rated for more than 10 years on Upwork | 🏆 70+ projects | 🏆 100% Job Success Score | 🏆 16 years experience | 🏆Working with 3x enterprise companies and so many start-ups/individual clients Production-grade computer vision systems for real-world environments — edge deployment, system integration, and measurable business outcomes. I graduated as an Electrical Engineer M.Sc. (Embedded Software Developer faculty). I am an expert in AI/Machine learning (object detection) and IoT/Edge Computing (Raspberry Pi and Jetson Orin NX/Nano, Deepstream 6.x, 7.x, Triton/TAO toolkit). I prefer long-term projects, but you can hire me for shorter ones also as a consultant. Strength: - Computer Vision/Machine learning Project architect/design - technical stack, cost of long-term usage, refine user requirement etc. - Python Machine learning projects (Tensorflow, Keras, PyTorch) - especially with computer vision, object detection (YOLO), image segmentation and pose tracking (OpenPose), shape recognition (dlib) and action recognition (X3D, mmaction etc.) - Develop/maintain/upgrade your existing Deepstream/Triton based application - Embedded image processing solutions (Edge computing): computer vision on Jetson Orin (NX/Nano) with Deepstream7.0 (earlier version too 6.x/7.x, Triton, TAO toolkit) or on Raspberry Pi, using Intel Movidius Neural Compute Stick (NCS) + OpenVINO. Train a model for specific purpose, provident dataset collection/preparation/preprocessing task management, I specialized for object detection (up to YOLOv12) - AWS, GCP (Google Cloud Platform) VM inference and training setup and execution/deployment - NVIDIA GPU experience: Tesla T4, L4, A100, H100 GPU for training and inference/server production. - Home automation/Smart home - lighting, building engineering, heating/cooling, Home assistant: integrate Amazon Alexa, Phillips Hue, Sonos, Apple TV, Google Nest, custom solutions - Raspberry Pi (Linux - Raspbian) - programming and teaching in Python (RS232, RS485, TCP communication), Wi-Fi settings, Home assistant Services: - Short (30-60 minutes) consultation - AI Architect tasks: responsible for the architecture of AI solutions, which includes planning, implementing, and managing AI technologies within an organization or project - I can speak English and Hungarian (magyar) and a little bit Spanish (castellano, espanol) AI Computer Vision | MLOPS | Edge Computing | AI Automation | AI strategy | AI consultant

Hello! My name is Aleksandr Kalinin. I have a double major in Math and CS. I have been programming professionally since 2006. Skills: C++ 11/14/17/20/23, STL, SIMD (SSE, AVX, AVX512), CMake, vcpkg, Conan, Boost, perf, VTune. Python, Data Science, NumPy, Pandas, Matplotlib. Rust, tokio. Algorithms, Data Structures, Computational Geometry, Optimization, Linear Algebra, Numerical Methods. Concurrent Programming, Multithreading, Lock-free Programming. CUDA, HIP, OpenCL, Compute Shaders, Halide, TBB, OneAPI. Graphics Programming, Vulkan, Metal, DirectX 12, OpenGL, HLSL, GLSL, MSL, Slang, Real-time Rendering, Custom Engine Development. Unreal Engine 4/5, Godot, Cocos2dx Machine Learning, Deep Learning, PyTorch, TensorFlow, Scikit-Learn, ONNX, TensorRT. Computer Vision, Image Processing, OpenCV, Roboflow, Triton, YOLO, YOLOv11, DETR, RT-DETR, Faster R-CNN, R-CNN, U-Net, DeepLabV3+, SAM, SAM2, SegFormer, ResNet, ConvNeXt, ViT, Swin. Optimization / Solvers: OR-Tools (CP-SAT), Z3, MiniSAT, SCIP, HiGHS, IPOPT, MiniZinc. Point Cloud Processing, Collision Detection, Physics Simulation. Maya API, Houdini API (HDK, VEX, HScript), Blender Python API, Pipeline Tools Development. Software Porting, Game Development. Qt, QML, PySide6, WxWidgets, VTK. iOS Development, Swift, Objective-C, UIKit, AVFoundation, Metal. Android Development, NDK. FFmpeg WebRTC, RTMP, RTSP, SRT, HLS, NDI, MPEG-DASH, CMAF, WebTransport, QUIC, UDP/RTP/RTCP, TCP, WebSockets, HTTP Live Streaming pipelines, Video Processing, Real-time Streaming Systems. JavaScript, Node.js, Three.js, Pixi.js. Docker, Kubernetes, AWS, EKS, CI/CD, n8n. PostgreSQL, Supabase. Windows, Mac, Linux. AI, Claude Code.