Hire the Best CUDA Consultants

Do you have an AI vision that needs to become a real, working product? I don't just build models; I engineer complete, scalable solutions that turn data into actionable insights and automation. For over five years, I've specialized in bridging the gap between cutting-edge Artificial Intelligence (AI) research and robust software that delivers real-world value. My core expertise lies in computer vision and machine learning, but my skill set is full-stack. This means I can own your project from the initial data pipeline, through model training and optimization, all the way to deploying a polished desktop application or a secure enterprise API. I thrive on building tools that work seamlessly for end-users, whether it's a retail manager, a traffic controller, or a sports coach. My strongest suit is developing intelligent systems that "see" and understand the world. I've built a retail analytics platform (CrowdIQ) that transforms standard CCTV into a source of business intelligence, tracking customer demographics and behavior. In the sports domain, I created PadelIQ, an analytics engine that uses computer vision to track player movement, posture, and court coverage from match footage, providing real-time coaching feedback. For public safety, I developed a traffic management system (OmniRoad AI) using advanced object detection for real-time accident and congestion monitoring. Beyond computer vision, I architect full-scale data science pipelines. A prime example is my telecom churn prediction project, where I built a machine learning model to identify at-risk customers and paired it with an interactive Power BI dashboard. This end-to-end approach—from data analysis to a clear visualization of insights—ensures the model's findings directly inform business strategy and retention actions. I also develop the tools and infrastructure that power AI applications. I've built secure, enterprise-grade systems like DevelmoGPT, a RAG-based LLM that allows for secure, semantic search over private company documents. From creating simple utilities like PDF-to-audio converters to designing complex role-based access systems, I ensure the foundation of any AI solution is reliable, secure, and maintainable. My process is collaborative and results-driven. I start by deeply understanding your business problem, not just the technical requirement. We'll then iterate through prototyping, development, and testing to ensure the final product not only meets specs but also delivers tangible ROI. I communicate clearly at every stage, providing demos and documentation so you're never in the dark. Let's connect. Share your project idea or challenge, and I'll provide a clear outline of how we can leverage AI, machine learning, or computer vision to build your intelligent solution. Click the invite button to start the conversation. /// The following is just for SEO. You can ignore it /// #computer vision #computer vision engineer #computer vision OpenCV #machine learning computer vision #deep learning computer vision #computer vision machine learning #machine learning python #nlp machine learning

Many computer vision models work in a notebook but fail in production. I build OCR, detection, and tracking systems that actually run in real environments so your team can automate workflows and extract real business value from visual data. I work with companies and startups who need robust AI pipelines for document automation, traffic monitoring, retail analytics, or custom visual AI applications. If you want a low-budget experiment with no clear success criteria, I’m probably not the best fit. 🔎 𝗛𝗼𝘄 𝗜 𝗪𝗼𝗿𝗸 𝟭. 𝗜𝗻-𝗗𝗲𝗽𝘁𝗵 𝗗𝗶𝘀𝗰𝗼𝘃𝗲𝗿𝘆 I begin each project by understanding your goals, constraints, and success metrics to ensure the solution meets your unique needs. 𝟮. 𝗠𝗼𝗱𝘂𝗹𝗮𝗿 𝗣𝗿𝗼𝗯𝗹𝗲𝗺-𝗦𝗼𝗹𝘃𝗶𝗻𝗴 I break complex tasks into smaller parts and test multiple approaches to find the most effective solution. This ensures reliable results you can trust. 𝟯. 𝗟𝗲𝘃𝗲𝗿𝗮𝗴𝗶𝗻𝗴 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 & 𝗖𝘂𝘀𝘁𝗼𝗺 𝗠𝗲𝘁𝗵𝗼𝗱𝘀 My toolkit includes all major computer vision tasks: Classification, detection, tracking, and segmentation. I combine off-the-shelf models with custom-built methods to achieve top-notch performance. 𝟰. 𝗖𝗹𝗲𝗮𝗿, 𝗙𝗿𝗲𝗾𝘂𝗲𝗻𝘁 𝗖𝗼𝗺𝗺𝘂𝗻𝗶𝗰𝗮𝘁𝗶𝗼𝗻 I keep you updated at every step, provide realistic timelines, and immediately address any hurdles. Even if you’re not technical, I’ll explain everything in plain language so you always know where your project stands. 𝟱. 𝗔𝗹𝘄𝗮𝘆𝘀 𝗣𝘂𝘁𝘁𝗶𝗻𝗴 𝗬𝗼𝘂 𝗙𝗶𝗿𝘀𝘁 My clients consistently give me 5-star ratings and glowing feedback. If your requirements stretch beyond my skill set, I’ll be transparent and let you know right away. 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗩𝗶𝘀𝗶𝗼𝗻 & 𝟯𝗗 𝗣𝗲𝗿𝗰𝗲𝗽𝘁𝗶𝗼𝗻 For projects involving robotics, autonomous systems, or spatial analytics, I also build 3D perception pipelines using LiDAR, stereo cameras, and point clouds. This includes 3D object detection, Bird’s Eye View (BEV) transformations, and point cloud processing using deep learning. 𝗥𝗲𝗰𝗲𝗻𝘁 𝗣𝗿𝗼𝗷𝗲𝗰𝘁𝘀 𝟭. 𝗠𝘂𝗹𝘁𝗶-𝗔𝗣𝗜 𝗢𝗖𝗥 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲: Combined Google Vision, OpenAI, and AWS Rekognition to increase document extraction accuracy across noisy images. 𝟮. 𝗦𝗰𝗮𝗻𝗻𝗲𝗱 𝗗𝗼𝗰𝘂𝗺𝗲𝗻𝘁 𝘁𝗼 𝗘𝘅𝗰𝗲𝗹: Parsed key fields using Python + QwenVL and auto-generated Excel reports. 𝟯. 𝗟𝗶𝗰𝗲𝗻𝘀𝗲 𝗣𝗹𝗮𝘁𝗲 𝗗𝗲𝘁𝗲𝗰𝘁𝗶𝗼𝗻: End-to-end system with YOLOv8 trained on custom dataset and deployed for inference 𝟰. 𝗥𝗲𝗮𝗹-𝗧𝗶𝗺𝗲 𝗟𝗶𝗗𝗔𝗥 𝗢𝗯𝗷𝗲𝗰𝘁 𝗗𝗲𝘁𝗲𝗰𝘁𝗶𝗼𝗻 & 𝗧𝗿𝗮𝗰𝗸𝗶𝗻𝗴 Built a 3D detection and tracking pipeline using LiDAR and camera data with 3D bounding boxes, frame-to-frame association, and 2D/3D visualizations for autonomous navigation. 𝟱. 𝗗𝗲𝗲𝗽 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗼𝗻 𝗣𝗼𝗶𝗻𝘁 𝗖𝗹𝗼𝘂𝗱𝘀 Trained PointNet and voxel-based 3D CNNs on ShapeNet Core for point cloud segmentation and classification, including full preprocessing and model visualization. 𝗧𝗲𝗰𝗵 𝗦𝘁𝗮𝗰𝗸 I work with Python, PyTorch, TensorFlow, OpenCV, YOLO, Open3D, and modern vision APIs (Google, AWS, OpenAI) to build detection, tracking, and OCR systems. 𝗪𝗵𝗮𝘁 𝗖𝗹𝗶𝗲𝗻𝘁𝘀 𝗦𝗮𝘆 "Yacine is reliable, very good at his job, and very informative. He was able to set up a POC, identify the main pitfalls, and propose solutions independently." "Yacine is committed to provide high quality work. He knows what he's doing. It's a pleasure to work together. I recommend him for data mining and vision work." "Yacine always does a great job on any computer vision related task, he delivered the project very quickly. I will definitely rehire him again whenever needed." 📬 Let’s Talk Send a message describing your computer vision problem and the data you’re working with. If it’s a good fit, we’ll discuss the next steps.

I help research teams and technical founders build and validate reliable, testable scientific and quantitative systems — research prototypes, backtesting frameworks, production execution systems, simulation engines, and performance-critical pipelines. I also conduct independent technical review of quantitative models and research frameworks. If you're dealing with slow code, messy data, a model you can't trust, or a research prototype that needs to become production, I can turn it into a robust, reproducible result. Background: PhD Physics (NYU, 2018). Quantitative Research at JPMorgan Chase — derivatives pricing on a 1M+ LOC C++ library. Max Planck Institute postdoc — general-relativistic hydrodynamics on 1,000+ core HPC clusters. 13 peer-reviewed publications, 1,300+ citations, h-index 12. WHAT I DELIVER ▸ Quant & Options Engineering Backtesting frameworks (event-driven or vectorized), walk-forward, leakage checks Options analytics: Greeks, IV surfaces, Black–Scholes and numerical methods Research → production pipelines (clean architecture, tests, logging, monitoring) Execution integrations (e.g., IBKR) and robust order / risk handling Market data ingestion, cleaning, corporate actions, quality control ML and statistical time-series models with proper cross-validation (no leakage) ▸ Scientific Computing & Research Tooling For physics, chemistry, biology, engineering, and any domain where the core problem is mathematical or computational. Custom numerical solvers (finite volume / finite difference, spectral, particle methods) with stability and convergence analysis Optimization engines (Bayesian, gradient-based, evolutionary) for experimental design, formulation, and parameter search Simulation frameworks from prototype to production grade Scientific data pipelines: ingestion, transformation, quality control, reproducible workflows Verification and validation: benchmarks, unit / regression tests, convergence studies Analysis tools, dashboards, and reporting infrastructure for research workflows Air-gapped and reproducible deployments where IP sensitivity or regulatory context requires it ▸ Quantitative & Mathematical Review (NDA-protected) Independent technical review of quantitative models, frameworks, and research Verification of internal consistency, identifiability, hidden assumptions, and mathematical correctness Assessment of whether the formal structure supports the conclusions drawn from it Implementation review against specification: numerical stability, edge cases, code-to-spec fidelity ▸ HPC & Performance Engineering Distributed computing (MPI / OpenMP / CUDA), GPU optimization, memory and I/O tuning Inference and training infrastructure at scale Profiling, refactors, and speedups for codebases that need to run reliably under production load WHY CLIENTS WORK WITH ME - Trustworthy work — research prototypes turned into tested, reproducible production code; models reviewed against their own claims - De-risking — failure modes surfaced early (leakage, overfitting, edge cases, scaling bottlenecks) - Maintainability — clean architecture, docs, handover-ready delivery your team can extend - Communication — clear milestones, concise updates, realistic timelines, no surprises - Math ↔ engineering bridge — strong intuition for both theory and implementation IDEAL PROJECTS - Quant strategy development, backtesting, and research infrastructure - Options analytics and derivatives tooling - Mathematical review of quantitative manuscripts, white papers, or research frameworks - Independent validation of production models against specification - Market data pipelines and reproducibility upgrades - Performance optimization of slow Python / C++ codebases - Distributed training, GPU optimization, and inference serving for ML workloads - Custom scientific or industrial simulation and numerical software - Internal R&D tooling for research labs and technical teams If this sounds like a fit, message me with a brief on your current setup and success criteria — I'll let you know how I can help.

Hello, I’m the founder of StreamTech, with over 11,000 hours across more than 100 AI and machine learning projects since 2016. I bring deep expertise in computer vision and edge AI ranging from object detection, tracking, and OCR to pose estimation, generative image processing, and event detection in sports feeds. I also excel in building intelligent AI agents and LLM driven chatbots that leverage multi turn dialog, RAG enabled memory systems, and API orchestration. My offerings extend beyond AI models and edge deployment. I provide full mobile experience solutions, creating cross platform React Native apps complemented by thoughtful UI/UX design. Whether it's crafting intuitive interfaces, responsive layouts, or seamless animations tailored for both iOS and Android, I ensure that the user experience complements the underlying AI technology. I guide projects end to end, collecting and labeling data, architecting and training models with PyTorch and TensorFlow, and deploying solutions either in the cloud (AWS, GCP) or on edge devices like Jetson Nano, Xavier, and Orin using DeepStream SDK. My engineering stack includes Python, C++, OpenCV, MediaPipe, OpenPose, SMPL, GANs, Stable Diffusion, Docker, and Kubernetes. At StreamTech, our mission has always been to harness cutting edge tech for meaningful business impact. By blending AI innovation with elegant mobile design, I help entrepreneurs and managers accelerate product development. If you're envisioning a mobile solution powered by CV or conversational AI, or need an AI agent interface that shines on mobile, let’s connect and explore how we can craft something exceptional together. Cheers!!

Experience in: Speech to Text Conversion Text to Speech Synthesis Natural Language Processing (NLP) Computer Vision and Neural Networks CUDA, PyCuda I'm a Machine Learning Engineer passionate about innovation and eager to work in Japan's technology sector. With expertise in various areas such as speech processing and GPU computing, I am looking for opportunities to contribute my skills in the Japanese market. I would also appreciate assistance with the work visa process for potential relocation. Feel free to reach out for collaboration or inquiries.

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.