Cudatrabajos

...privada con mi entorno de agentes desde cualquier dispositivo móvil/celular sin exponer el servidor a riesgos. #### **Requisitos del Freelancer:** * Experiencia sólida con **Ollama**, frameworks de agentes (**OpenClaw**, LangChain/LangGraph o similares) y automatización en **n8n**. * Dominio avanzado de entornos Linux (Debian/Ubuntu/Pop!_OS), gestión de puertos y asignación de recursos GPU (NVIDIA CUDA). * Experiencia implementando túneles de red seguros (Reverse Proxies / Tunnels). * Capacidad para entregar código limpio en Python/Bash y documentar brevemente los puertos asignados a cada servicio. Si tienes experiencia montando este tipo de ecosistemas locales eficientes y rápidos, por favor postúlate detallando...

Desarrollo e implementación del sistema RoadGuard (Alcance Técnico MVP según Anexo NDA). • Entorno: Desarrollo Headless (SSH/CUDA) en servidor con GPU RTX 3090. • Modelos: Implementación de YOLOv8/v10 para detección de baches, grietas y señales, incluyendo preparación de dataset y ajustes de entrenamiento. • Tracking: ByteTrack para evitar duplicidad de registros. • Georreferenciación: Sincronización de Timestamps vs Logs GPS (interpolación lineal y compensación OFFSET_MS). • Entregables: Pipeline funcional integrado y código fuente documentado.

...corre sin interrupciones perceptibles. El proyecto consiste en el desarrollo de un motor de inferencia de alta performance para la detección, clasificación y seguimiento de múltiples clases de objetos en entornos dinámicos complejos, utilizando hardware dedicado. Implementación de arquitecturas de detección (YOLO/RT-DETR) y algoritmos de tracking.• Optimización de modelos para hardware NVIDIA (CUDA/TensorRT).• Fusión de datos provenientes de sensores externos (Telemetría/GPS) con flujos de video 4K.• Desarrollo de lógica de persistencia en bases de datos geoespaciales. • Seniority comprobable en Python y OpenCV. Experiencia en el ciclo completo de vida de modelos de visión: desde ...

...Engineer - Real-time Edge AI (OpenCV, ONNX, CUDA & TensorRT) Busco un Senior Computer Vision Engineer con experiencia demostrable en Edge AI para desarrollar un sistema de asistencia táctica en tiempo real basado en captura de vídeo externa. Desafío Técnico Principal: El sistema debe procesar un flujo de vídeo HDMI, realizar OCR de alta precisión y detección de objetos, y consultar una base de datos local con una latencia end-to-end inferior a 100ms. Stack Tecnológico Requerido: • Lenguaje: Python 3.10+ con arquitectura OOP escalable (Interfaces abstractas). • Visión: OpenCV avanzado y procesamiento de imágenes para OCR de stacks y botes. • Motores de Inferencia: Experiencia obligatoria con ...

Instalar CUDA, Cudnn, PyTorch para proyecto de Python YOLOv5

Necesito instalar y compilar un programa que es público en mi Ubuntu 20.04.

Hola, Mi hijo busca ayuda con un trabajo: Implementar el algoritmo de multiplicación de matrices con números en coma flotante en las librerías paralelas OpenMP, OpenMPI y CUDA utilizando un ordenador sobremesa. Tareas a realizar: - Implementación en un multiprocesador usando OpenMP - Implementación en un multicomputador usando OpenMPI - Implementación en un coprocesador de tipo GPU usando CUDA - Evaluación de prestaciones usando contadores hardware

Hola Diego, Mi hijo busca ayuda con un proyecto, puedes ayudarlo? Implementar el algoritmo de multiplicación de matrices con números en coma flotante en las librerías paralelas OpenMP, OpenMPI y CUDA utilizando un ordenador sobremesa. Tareas a realizar: - Implementación en un multiprocesador usando OpenMP - Implementación en un multicomputador usando OpenMPI - Implementación en un coprocesador de tipo GPU usando CUDA - Evaluación de prestaciones usando contadores hardware

Buenas tardes marlon, hemos hablado recientemente sobre un trabajo de cuda y openmp, si me das garantía de que me lo haces en menos de 10 días te pagaré lo que me propusistes 24 euros. Gracias. Saludos

Necesito que desarrollen un software para mí. Me gustaría que este software sea desarrollado.

tengo que hacer trabajo openmp y cuda

Hola necesito hacer trabajos de c, omp,cuda.

Cuda , programacion paralela

Otra o no estoy seguro Python Solicito programadores con conocimientos en CUDA

Hola José. Necesito una mano para implementar en CUDA una serie de funciones que tengo escritas en C++. Mayormente manipulación de matrices para entrenamiento de redes neuronales, deep learning. La idea es implementarlas en una DLL CUDA (para que se ejecute en la GPU) y llamarlas desde Excel VBA. Estamos hablando de unas 300 lineas de código (una vez eliminados huecos y comentarios). Pásame, por pavor, una estimación o tarifa horaria, si te interesa el trabajo. Gracias.

Hola Juan. Necesito una mano para implementar en CUDA una serie de funciones que tengo escritas en C++. Mayormente manipulación de matrices para entrenamiento de redes neuronales. La idea es implementarlas en una DLL CUDA (para que se ejecute en la GPU) y llamarlas desde Excel VBA. Estamos hablando de unas 300 lineas de código (una vez eliminados huecos y comentarios). Por cierto, somos colegas, yo también soy ingeniero aeronáutico. Pásame, por pavor una estimación o tarifa horaria, si te interesa el trabajo. Gracias.

Hola allenross356, vi tu perfil y me gustaría ofrecerte mi proyecto. Podemos conversar los detalles en el chat. I'd like to have a simple neural network(3 layers) in CUDA 8 using the back propagation.

Necesito convertir un proyecto que tengo de un algoritmo de compresión de texto llamado lzw a CUDA y que tenga un speed up de al menos 10 veces. Referencia que puede ser de utilidad:

...paralelizar el código siguiente que corresponde al método de jacobi, hecho en C/C++ en cada uno de los paradigmas (memoria compartida (openMP), Memoria distribuida (MPI) y uso hibrido (CUDA). En el código se deben indicar (con comentarios) las partes paralelizadas . En un archivo en pdf, debera decirme como se debe compilar y correr cada archivo, y que tanto esta acelerando su solución con respecto al original que se le envia. (por ejemplo, puede analizar cuanto tiempo se demora en ejecutarse en la versión secuencial que le envío vs cuanto tiempo en cada una de las versiones paralelas (openMP, MPI, cuda). Puede ser en una gráfica de comparación. Adjunto el código en un archivo de texto, el códig...

Por favor, regístrate o inicia sesión para ver los detalles.

Tenemos una aplicación y deseamos programar, utilizando C++, OpenCV, CUDA. En la actualidad está desarrollado en ambiente LabView  * Categoría: IT & Programación * Subcategoría: Desktop Applications * Es un proyecto o una posición?: Un proyecto * Actualmente tengo: Tengo el diseño * Experiencia en este tipo de proyectos: Si (He administrado este tipo de proyectos anteriormente) * Disponibilidad requerida: Tiempo completo * Integraciones de API: Otros (Otras APIs) * Plataformas requeridas: Windows

...Data visualization - Charting libraries, dashboards, S-curve and trend charts - Preferred Report generation - PDF, Excel, Word, PowerPoint export - Preferred ML / AI Infrastructure PyTorch & Hugging Face - Model fine-tuning, PEFT/LoRA, Transformers library - Preferred Voice / speech ML - STT, TTS, end-to-end voice pipeline development - Preferred GPU infrastructure - Self-hosted GPU servers, CUDA, resource monitoring - Preferred Inference serving - High-throughput model serving, quantization, optimization - Preferred Evaluation - Standard and custom domain-specific evaluation harnesses - Preferred Infrastructure & DevOps Docker - Containerization, multi-stage builds, compose - Preferred CI/CD pipelines - Automated build, test, security scan, deployment workflo...

...ZCHSound dataset. • Integrate MMT and the cosine-guided attention cleanly into PyTorch so each component can be toggled on/off for ablation. • Train, validate and test on the official ZCHSound splits, reporting multi-class metrics (accuracy, F1, AUC) and benchmarking against at least two published baselines. Deliverable checklist 1. Fully documented Python/PyTorch codebase (compatible with CUDA) that downloads/reads the dataset, preprocesses PCG audio into spectrograms, builds the Transformer-MMT network, trains, and outputs metrics. 2. Saved best model weights plus an inference script that takes a new .wav file and returns a predicted class with confidence. 3. Concise technical report (Markdown is fine) summarising feature-extraction rationale, architectur...

...Model/Workflow → Parse → Filter → Track → Game-Specific Analysis → Visualization IMAGE PROCESSING Support: Capture → ROI/crop → Resize → Color conversion → Normalization → Inference → Postprocessing ROI should be configurable where it improves performance. Input sizes such as 640×640 and 960×960 should be benchmarked for the target hardware. GPU OPTIMIZATION Where supported, evaluate: • NVIDIA CUDA • FP16 • TensorRT • GPU preprocessing • Asynchronous inference • Efficient memory transfer • CPU/GPU synchronization Use measured benchmarks rather than unnecessary optimization. GUI Create a modern Windows GUI that controls the real system. Display: • Game/profile &b...

...generally allows the system to keep up more easily. 18. End-to-end latency CV latency is only one part of the total chain: Controller input → PS5 → Remote Play → video encoding → network → decode/capture → CV → display Therefore: CV latency ≠ total game latency A CV pipeline cannot reduce Remote Play or network latency to zero. 19. GPU inference On supported NVIDIA hardware, model inference can use CUDA and FP16. This can reduce memory use and improve throughput, but the result depends on the GPU and workload. 20. Image size YOLO input size affects the speed/detail tradeoff: 640×640 → generally faster, less detail 960×960 → generally slower, more detail The goal is to balance accuracy and latency for the actual har...

...bank. The ideal path will use a completely free or very low-cost AI tool—something along the lines of DeepFaceLab, FaceFusion, or any other desktop solution you trust that runs smoothly on Windows. Here is what I need from you: • Help me choose the right Windows-compatible application that is either free or extremely affordable. • Guide me through installation and all necessary dependencies (CUDA, Python, GPUs, codecs, etc.). • Walk me step-by-step through preparing source footage, training the model, swapping faces, and exporting the final video. • Provide simple troubleshooting tips so I can fix common errors on my own. • Deliver a concise cheat-sheet or screen-recorded tutorial so I can repeat the process later. Acceptance criteria ...

...with the robot’s existing control system. * Identify the existing API, SDK, ROS interface, middleware, or function-calling mechanism used between the LLM and robot control. 2. Deploy a local GPT-2B model * Select an appropriate ~2B parameter model suitable for local inference. * Deploy it on the robot’s onboard NVIDIA GPU. * Use GPU-accelerated inference (TensorRT-LLM, CUDA, vLLM, or another appropriate optimized runtime). * Optimize the model for low latency and reasonable memory/compute usage. 3. Connect GPT-2B to the existing robot interface * Do NOT rewrite the existing motor-control system. * Do NOT develop new low-level motor drivers. * Do NOT replace the existing Unitree SDK / motion-control implementation. * Instead, make t...

...research & selection: advise on the most suitable architectures (YOLO-v8, Faster R-CNN, DETR, or anything you feel is a smarter fit). • End-to-end development: data preprocessing, augmentation, training, validation, and hyper-parameter tuning using Python with TensorFlow or PyTorch plus essential OpenCV utilities. • Performance optimisation: achieve fast inference on both GPU and edge devices (CUDA / TensorRT knowledge is a big plus). • Deployment wrapper: export to ONNX or TensorFlow-Lite and integrate a simple API or demo app so I can test detections live. • Knowledge transfer: clean, well-commented code in a private repo, plus a short hand-off session (recorded or live) so future iterations are straightforward. Acceptance criteria – mAP...

... — but with a closed, gaming-style enclosure and a proper integrated power button. Primary use: running AI image-recognition models locally. I'll handle all AI software myself — this job is hardware only: choosing the parts, building the unit, and delivering it with Windows installed and drivers working. The main thing this affects for you is component choice: an NVIDIA dGPU with CUDA support and as much VRAM as the budget allows is the priority. Secondary goal: noticeably cheaper than an equivalent desktop PC while staying close in performance. Deliverable One fully assembled, tested, working unit shipped to me, plus a parts list, wiring diagram, photos of the internals before closing the case, and a short setup/maintenance guide. Core components Laptop motherbo...

I need someone to jump on AnyDesk or TeamViewer and turn my Windows 11 desktop with an NVIDIA GPU into a fully portable DeepFaceLive box. Start by checking which CUDA toolkit is already present—I honestly don’t know—then install or upgrade whatever version best matches the GPU and DeepFaceLive’s current build. Once CUDA is sorted, set up a clean, self-contained (no system-wide edits) Python environment; I’m flexible on the exact 3.x version as long as every required library plays nicely with the GPU. Finish by enabling the virtual camera so I can push the swapped feed into Zoom, OBS or Discord without additional tweaks. Acceptance test • Launch DeepFaceLive from the portable folder you create • Load a sample model and run a live...

My 3D scanner streams PCD point-cloud files that contain spiral-shank bolts mixed with other hardware. I need a compact, CUDA-friendly C++ solution that runs directly on an NVIDIA Jetson Orin NX, spots every bolt in each cloud, records the head-center XYZ (and, if practical, its axis direction), and writes the results to a structured XML file. Performance targets • Accuracy: at least 95 % correct identification on the annotated dataset I will supply. • Speed: real-time or near real-time processing on the Orin NX under the standard JetPack image. You are welcome to build on open-source libraries such as PCL, Open3D, Eigen, cuBLAS or TensorRT, provided everything can be compiled through CMake and redistributed without license issues. Deliverables • Well-doc...

...current prompt chains and function calls to pinpoint exactly where Claude Code and Ollama are over-allocating tokens. • Concrete code-level optimisation techniques—prompt refactoring, context window trimming, token-length guards, caching strategies or any other proven methods—that cut the total daily tokens consumed. • Configuration tweaks for both my local machine and the remote H200 server (CUDA, model quantisation, batching, concurrency limits, etc.) so performance improves instead of degrading. • Suggestions for alternative tools, models, or routing logic if replacing parts of the stack would save more tokens than patching them. Deliverables I’d like to see: 1. A brief report that highlights every hotspot you find, shows before-/afte...

I am rapidly up-skilling in CUDA C++ and want an experienced mentor who can walk me through the real-world use of the core foundational libraries—Thrust, CUB, and libcudacxx. My main need is to see clean, well-explained example implementations and concrete use cases rather than abstract theory. Here is what I have in mind: • Short, focused code samples that highlight best-practice patterns in each library (device vectors, reductions, custom kernels, cooperative groups, etc.). • Step-by-step explanations of how these examples map to GPU execution, memory hierarchies, and performance considerations. • Guidance on how to slot each snippet into an existing CMake-based project so I can experiment immediately. I already have a CUDA 12.x toolchain set u...

...statistics and performance monitoring Responsibilities - Designed the architecture for the decentralized AI compute network. - Developed backend services for GPU worker registration, workload management, and job orchestration. - Implemented the communication layer between the central coordination services and distributed GPU workers. - Built AI execution services capable of running workloads on CUDA-enabled GPUs. - Designed the compute accounting and miner reward workflow. - Integrated blockchain functionality for transparent contribution and reward tracking. - Developed APIs for managing users, workers, jobs, compute resources, and rewards. - Implemented real-time monitoring of GPU workers and workload execution. - Containerized AI workers and supporting services using Docker....

...already flashed, updated, and running smoothly—now I need Autoware up and working end-to-end on it. I’m targeting the Perception, Localization, and Path Planning stacks, so the job is to install, configure, and validate those three modules on the board. Here’s what I expect: • Clean installation of the current Autoware version compatible with JetPack on the AGX • All required dependencies (ROS 2, CUDA, TensorRT, etc.) resolved without breaking existing packages • Perception, Localization, and Path Planning nodes launched through reproducible, scripted workflows (Docker or native—your call, as long as it’s reliable) • Demonstration bag file or simulation run proving each module is publishing the right topics at expected rate...

I need an experienced PyTorch/CUDA engineer to squeeze every practical second out of our ROLLCALL Wan 2.2 I2V A14B inference pipeline running on an A100 80 GB while keeping the pictures looking exactly the same. Reducing processing time is the prime objective; any change that simply trades speed for a worse image will be rejected. The first job is a deep profile. Please time each phase separately—model loading, T5/text encoding, VAE, diffusion, decoding, FFmpeg, and all inter-segment overhead—so I can see exactly where the pipeline stalls. From my own sampling it looks as if models may be re-opened for every 5-second chunk, so post-processing and segment overhead are the first areas I’d like you to attack. Once the slow spots are confirmed, create a persistent wa...

...Data visualization - Charting libraries, dashboards, S-curve and trend charts - Preferred Report generation - PDF, Excel, Word, PowerPoint export - Preferred ML / AI Infrastructure PyTorch & Hugging Face - Model fine-tuning, PEFT/LoRA, Transformers library - Preferred Voice / speech ML - STT, TTS, end-to-end voice pipeline development - Preferred GPU infrastructure - Self-hosted GPU servers, CUDA, resource monitoring - Preferred Inference serving - High-throughput model serving, quantization, optimization - Preferred Evaluation - Standard and custom domain-specific evaluation harnesses - Preferred Infrastructure & DevOps Docker - Containerization, multi-stage builds, compose - Preferred CI/CD pipelines - Automated build, test, security scan, deployment workflo...

...that Wan2.2 A14B can generate usable video on an NVIDIA A100 80GB. The previous prototype used RunPod, Python, PyTorch/CUDA, FastAPI/Uvicorn and FFmpeg, but I do not want to continue patching a fragile experimental environment. The engineer may recommend RunPod, Lambda Cloud, CoreWeave, AWS/GCP/Azure or another appropriate GPU provider, but must justify the choice specifically for a large Wan2.2 A14B workload. Required architecture: ROLLCALL Website → API → Persistent Job Queue/Database → Disposable GPU Worker → Wan2.2 I2V A14B → FFmpeg/QC → Object/Persistent Storage → ROLLCALL Requirements: NVIDIA A100/H100-class production inference Wan2.2 I2V A14B Python/PyTorch/CUDA reproducible Docker-based deployment pinned/compatible dependenc...

Senior AI Video / GPU Engineer Needed – Wan2.2 + RunPod A100 + PyTorch/CUDA I need an experienced AI/GPU engineer to finish and productionize an existing AI video-generation backend for a platform called ROLLCALL. This is NOT a website design job. The website is already built. I need someone who specializes in GPU inference, Python, PyTorch/CUDA environments, AI video models, and production API deployment. CURRENT SYSTEM We already have: RunPod NVIDIA A100-SXM4 80GB GPU Wan2.2 I2V A14B Approximately 118GB of Wan2.2 model files already downloaded Persistent /workspace storage Python PyTorch/CUDA FastAPI/Uvicorn worker FFmpeg Existing website integration Existing REST API running on port 3010 Current API routes include: GET /v1/health POST /v1/generate GET /...

...premium platforms). Server Hardware & Environment OS: Ubuntu 26.04 LTS CPU: Intel Core Ultra 9 285K (24 Cores / 24 Threads) GPU: NVIDIA GeForce RTX 5090 (32 GB VRAM, Driver 595.84, 575 W power limit) RAM: 60 GB System Memory Storage: 2 TB Samsung 9100 PRO NVMe SSD Key Responsibilities & Scope of Work Server Setup & Stack Configuration: Complete Ubuntu environment setup optimized for PyTorch, CUDA, and high-vram local inference. Deployment and tuning of ComfyUI, Open WebUI, and n8n. AI Character & Video Production Pipeline: Build advanced ComfyUI workflows leveraging SOTA open-source video/image models. Implement character consistency tools using LoRAs and IP-Adapter/ControlNet pipelines. Integrate lip-sync and dialogue tools (e.g., LivePortrait, MuseTalk, Eleve...

Our NVIDIA CUDA-based servers are online but still missing a production-ready software stack. I need the environment installed, tuned, and kept rock-steady so my research team can start running heavy models without delays. Scope • System setup & configuration – install the latest CUDA toolkit, drivers, cuDNN, NCCL and required OS dependencies, then provision Docker/Container runtime so future upgrades are painless. • Performance optimization – profile current throughput, adjust BIOS, kernel, power and GPU settings, implement mixed-precision or other CUDA tweaks, and document the gains with repeatable benchmarks. • Ongoing maintenance & troubleshooting – create health-checks, monitoring hooks (Prometheus/Grafana preferred)...

I’m expanding a high-performance computing initiative and need seasoned C/C++ talent to squeeze every last cycle out of our code. The core of the work revolves around designing, profiling, and hardening parallel processing routines that will run on Linux/Unix clusters. You’ll be free to choose the right mix of pthreads, OpenMP, MPI, CUDA, or similar frameworks as long as the end result is fast, deterministic, and fully verifiable. Here’s the environment you’ll step into: a mature codebase written almost entirely in modern C and C++, backed by rigorous data-structure design, multithreaded execution, and an SDLC that values deep debugging over quick patches. I handle planning, testing resources, and CI; you focus on writing clean, well-documented modules and d...

...them. • A fraud-detection layer that flags suspicious listings or bidding patterns before a transaction closes. Everything must sit behind a clean, minimal interface—no clutter—because both food and pharmaceutical professionals will be using it every day under time pressure. I’m open on stack, but Python with TensorFlow/PyTorch for the models and a lightweight React or Vue front end makes sense; CUDA optimisation is a plus for the Inception pitch. Acceptance criteria for the MVP: 1. End-to-end workflow: seller upload → AI price suggestion → live auction → automated & manual bids → secure checkout. 2. Latency for price predictions under two seconds on a single Nvidia GPU. 3. Admin dashboard that surfaces fraud alerts and key mar...

...Demo Dashboard Requirements A simple web dashboard should include: Live Camera View AI Detection Overlay Event Alerts Event History Detection Screenshots Camera Management (Basic) Dashboard Statistics A polished UI is preferred but not mandatory for the demo. Preferred Technology Stack Python FastAPI YOLO OpenCV TensorFlow or PyTorch React.js PostgreSQL Docker Ubuntu Linux NVIDIA GPU Support (CUDA) Equivalent technologies are acceptable if performance and scalability are maintained. Future Scope If the demo is approved, the selected developer/team will continue with the complete platform development, including: Face Analytics Safety Analytics Vehicle Analytics Object Analytics Attendance Analytics Multi-location Dashboard Mobile Application Notifications (Email, WhatsApp,...

...on my side. • Deliver the trained model file, an inference script or API endpoint, and a brief report explaining your methodology, final accuracy, and any recommendations for future improvements. I will supply the images and their class labels as soon as we start, and I’m happy to discuss target accuracy or class-imbalance strategies up front. The code should run on a standard GPU instance (CUDA 11.x). Once the model meets the agreed accuracy on my held-out validation set, the project is finished and paid in full....

We are installing EDGE AI devices — mainly NVIDIA JETSON series and higher power units in jails and prisons to detect inmate activity. We need someone familiar with setting up these devices. NVIDIA Jetson™ modules deliver accelerated AI performance at the edge. With the NVIDIA JetPack™ SDK, you can develop and deploy innovative products across industries. The Jetson family uses unified NVIDIA® CUDA-X™ software and supports cloud-native technologies for streamlined AI development and deployment. These prisons and jails often have different routers, securuty and networking. We need experience here to get the message stream from the NVIDIA devices to the Cloud management system.

Looking for an experienced CUDA/C++ developer for short GPU optimization and debugging tasks. Work will require: Direct work on my development environment via AnyDesk/TeamViewer. Tasks include debugging CUDA kernels, fixing tensor indexing issues, improving performance, and optimizing GPU usage.

CUDA Developer Needed – Long-Term Remote Work (AnyDesk/Remote Access) I am looking for an experienced CUDA/C++ developer to help me complete GPU optimization tasks. This is a long-term collaboration opportunity for someone with strong experience in CUDA kernels, PyTorch, and performance optimization. Work setup: Remote work through AnyDesk or another remote desktop tool. You will work directly on my development environment. Tasks involve debugging, improving, and optimizing CUDA implementations. Each task typically requires around 3 hours of focused work. Payment: Rate: $8–$10 per hour depending on experience. Payment will be released after 2 weeks of completed work. This is intended to become a long-term working relationship with regular ta...

I need a Senior Computer Vision and Deep Learning Engineer to build a complete production-ready AI background removal system for AKPRINTHUB, with qualit...third-party paid API should be used. The developer will be responsible for the complete project, including AI model selection/fine-tuning, Python FastAPI backend, GPU optimization, frontend integration with my existing PHP/JavaScript website, testing, bug fixing, deployment and production launch. Required technologies include Python, PyTorch, OpenCV, image segmentation, alpha matting, ONNX/TensorRT, CUDA, Docker and GPU deployment. Complete source code, trained model weights, training scripts, deployment files and documentation must be handed over. Payment will be milestone-based after quality and speed testing against a privat...

CUDA Developer Needed – Long-Term Remote Work (AnyDesk/Remote Access) I am looking for an experienced CUDA/C++ developer to help me complete GPU optimization tasks. This is a long-term collaboration opportunity for someone with strong experience in CUDA kernels, PyTorch, and performance optimization. Work setup: Remote work through AnyDesk or another remote desktop tool. You will work directly on my development environment. Tasks involve debugging, improving, and optimizing CUDA implementations. Each task typically requires around 3 hours of focused work. Payment: Rate: $8–$10 per hour depending on experience. Payment will be released after 2 weeks of completed work. This is intended to become a long-term working relationship with regular ta...