Hire the Best CUDA Developers

If you can think of a problem, I can engineer the solution. My career has been built on tackling projects where mathematics, performance, and reliability collide. From deep computational geometry to real-time imaging pipelines and AI breakthroughs, I bring algorithmic thinking into production-grade systems. What I Make Possible Computational Geometry & Simulation (CUDA): Architected a real-time electric field line simulator on GPUs, handling the dense math behind vector fields and parallel kernels. Delivered BIM-style geometry evaluation and Bezier-based drawing tools for clients who needed accuracy, interactivity, and stability at scale. Interactive Geometry Tools: Distinguished performer in delivering CAD-like solutions — room planning engines, floorplan canvases, and curve editors that match the sophistication of industry BIM systems. AI/ML (Computer Vision & OCR): Outperformed Tesseract and other baselines in image classification and OCR by building custom ML.NET and PyTorch pipelines. Leveraged trained models for chemistry-focused OCR, decoding molecular diagrams and classifying scientific data that generic engines couldn’t touch. MVVM & Real-Time Imaging: Built a live-view imaging pipeline in C#/WPF with sub-30ms latency, sustaining real-time overlays without freezing the UI by combining async/await with multithreading. I’m not just about ViewModels and data binding — I handle what most developers would call impossible to fold into MVVM, structuring complex rendering logic, continuous device streams, and performance-critical updates cleanly into responsive applications. Backend Architecture (ASP.NET Core): Built a search engine that transformed OCR’d exam content into queryable data for JEE/Olympiad problems, returning matches and solutions with precision. Secured APIs with Microsoft Identity + JWT for robust user management. XAML Engineering: Designed custom bindable controls — battery meters, temperature indicators, sound meters — powered directly by live camera and device data. Beyond templates, I create reusable controls that extend the XAML ecosystem. Algorithm Design: From extracting clean outlines from noisy contours to detecting bonds in chemical structures, I specialize in solving problems where raw data needs to become usable intelligence. Security & DevOps: Full-stack capability in authentication/authorization, user management APIs, and CI/CD pipelines to keep delivery seamless and production-ready. Beyond the Obvious If you can imagine extracting complex geometrical details from a live camera feed, training an AI model on that data, and rendering it in real-time with OpenGL/WebGL/WPF — I can deliver it or even make it interactable. This is just a mad example; the possibilities are much wider — not limited to camera or geometry, but really about what you can imagine when these skills combine, powered by my foundation in mathematics, computational geometry, CUDA, and AI. Recognition I am Expert-Vetted on Upwork, officially ranked among the top 920 freelancers worldwide in 2024 — a distinction far more selective than “top 1%.” This represents consistent success on high-stakes, algorithm-heavy projects with global clients. Skills & Tools C#, .NET, ASP.NET Core, REST APIs, Microsoft Identity, JWT Authentication, SignalR, EF Core, LINQ, MongoDB, Azure, Docker, Microservices WPF, WinUI 3, UWP, Uno Platform, MAUI, XAML, Custom Controls, MVVM, Real-Time Imaging, UI/UX for Desktop C++, CUDA, GPU Acceleration, High-Performance Computing (HPC), Parallel Computing, OpenGL, GLSL, CUDA-OpenGL Interoperability Computational Geometry, Physics Simulation, Algorithm Design, Contour Extraction, Data Structures & Optimization Machine Learning, Deep Learning, Computer Vision, OCR, Data-Driven Modeling, PyTorch, TorchVision Performance Optimization, Clean Architecture, Multithreading, Async/Await, CI/CD Pipelines, DevOps

Machine Learning and AI Engineer. 8+ years shipping applied AI into production: LLM agents and RAG, NLP, speech, computer vision, and CUDA. I build systems that hold up in production, not demos, and every claim below is a number I measured. LLM and NLP - Semantic CV-to-job matching for an EU job board: 10,001 CVs against 10,003 vacancies, 100M cosine pairs in about 18s on one RTX 4090 (bge-m3), then a two-stage LLM re-rank that spreads the top 10 from 0.93 down to 0.71 where the raw cosine moves only 0.03. - LLM CV builder: messy PDF / DOCX / LinkedIn text into a strict Pydantic record bound to the client's 674-value taxonomy, so invalid output is structurally impossible. Emits a recruiter-ready LaTeX PDF and database-ready JSON. - Crypto signals from tweet embeddings (live client program): Qwen3-Embedding-8B on an A40, 1M+ tweet vectors in Qdrant, 44 symbols scored every 60 seconds, 4.65M events ingested, 10-day zero-error run. Speech - On-prem call-centre speech-to-text, in production 2020-2022, feeding fraud detection and call routing. Benchmarked on hand-labeled calls: Whisper 20% median WER, Vosk 28%, Google 32%. - Diarized transcription toolkit, TTS, and cloned-voice agents. Computer vision and CUDA - Multi-camera 3D capture for film relighting: 33 datasets delivered, 3-32 synchronized cameras each, GPU space carving at 1.98 s/frame versus 65 s in vectorized NumPy (about 33x). 5.0 Upwork review. - GPU brute-force passphrase recovery: about 58,000 candidates/s on one RTX 4090, 160x over CPU, sharded across multiple GPUs and machines. - Open-set retail robot vision on ROS 2; banknote detection at the cash desk. YOLO, Grounding DINO, RealSense. How I work Anti-hallucination is enforced in the code path, not in a prompt: strict schema validation, retry on violation, closed enum vocabularies. Success criteria are pre-registered before results exist, models are judged on time-ordered splits, and negative results get reported rather than buried. Stack - LLM and agents: OpenAI API, Claude Agent SDK + MCP, LangChain / LangGraph, RAG, vLLM, Hugging Face Transformers, fine-tuning, structured outputs with Pydantic + instructor, hand-written tool-use loops, chatbots on Telegram and web - NLP and search: embeddings, semantic search, vector databases (Qdrant), clustering, topic discovery, classification, multilingual pipelines - Speech: Whisper, Vosk / Kaldi, Deepgram, Google Cloud STT, TTS, speaker diarization - Vision: OpenCV, YOLO, Grounding DINO, TensorFlow Object Detection, RealSense RGB-D, ROS 2, NVIDIA Jetson - Classic ML: PyTorch, TensorFlow, scikit-learn, CatBoost, forecasting, time-series validation, reinforcement learning - GPU: CUDA C++, PyCUDA, Nsight Compute, multi-GPU sharding - Data and infra: Python, FastAPI, Docker Compose, PostgreSQL, Redis, BigQuery, pandas / NumPy / Parquet, n8n, Linux VPS, GCP Full case studies for each project above, with architecture diagrams and honest results including what did not work, are in my Portfolio section below. Tell me what you are building and I will tell you plainly whether I am the right fit for it.

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.

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. MATLAB, SageMath, Mathematica. Graphics Programming, Vulkan, Metal, DirectX 12, OpenGL, HLSL, GLSL, MSL, Slang, Real-time Rendering, Custom Engine Development. Unreal Engine 4/5, UE5 (3D, PCG, Geometry Scripting, Control Rig, Niagara, UMG, Slate, GAS, Chaos Cloth), 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, JUCE, 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.

I build production-ready AI systems for businesses that want to automate workflows, integrate LLMs, and launch reliable AI features — not just demos. My core work includes RAG applications, AI agents, chatbots, workflow automation, FastAPI backends, Dockerized deployments, and cloud-based AI integrations using OpenAI, LangChain, Python, and vector databases. Most AI developers can connect an API. Very few can ship a system where the AI behaves reliably under real-world constraints. That's the gap I fill. 🎯 I help businesses integrate AI into their workflows and deliver practical solutions that solve real problems. 🚀 What I've Actually Shipped: ✅ A full agentic pipeline that extracted structured clinical trial data from unstructured medical PDFs and published HL7 FHIR resources via REST API — reducing manual extraction time by ~70% ✅ A Clinical Decision Support System for heart failure — processed unstructured doctor notes, extracted 10+ clinical parameters via NLP, and generated GPT-4-powered treatment recommendations with safety constraints ✅ A FastAPI-based quantitative research platform — modular backend handling market data ingestion, backtesting, optimization, and AI-assisted report generation for an international client ✅ A Cloud-Native LLM Inference System — OpenAI-compatible endpoint using vLLM and Modal GPU infrastructure, sub-200ms latency 🧠 Where I'm Genuinely Different: Healthcare AI is my sharpest edge. HL7 FHIR, AWS Comprehend Medical, clinical NLP — this stack is rare. If you're building anything touching medical data, patient workflows, or clinical AI, you won't find many engineers at any level who've shipped in this exact space. I also treat AI output with engineering discipline. I know when a model is hallucinating a field name. I know when structured output needs schema-controlled prompting to be safe. I build fallbacks, not faith. 🔒 ⚙️ Tech I Work With Daily: Python · FastAPI · Flask · Streamlit · OpenAI API · Google Gemini · AWS Comprehend Medical · HL7 FHIR · NLP · REST APIs · Docker · PostgreSQL · GitHub · Prompt Engineering · LLM Workflows 🤝 I Work Best With Clients Who: → Have a real problem, not just a vague AI curiosity → Want production-ready systems, not toy prototypes → Value clear communication and zero-surprise delivery 📩 Send me a message describing what you're building. If it's a fit, I'll tell you exactly how I'd approach it — before you commit to anything.

🚀 I Build Scalable Software Systems That Don’t Break When You Grow Most developers write code. I design systems that survive scale. With 5+ years of experience as a Full-Stack & AI/ML Engineer, I architect and deliver high-performance systems used by global users, from AI-driven platforms to enterprise-grade distributed systems. 💡 What I Help You Achieve 🏗 Enterprise-Grade Architecture Scaling is not about adding servers later. It is about designing the right foundation from day one. I design: • Microservices and event-driven architectures • High-availability distributed systems • Horizontal auto-scaling infrastructure • Zero-downtime deployments • Load balancing and intelligent caching • Rate limiting and anti-DDoS strategies • Multi-tenant SaaS architecture Tech stack: • FastAPI, Django, Flask, Express.js, NestJS • Go, Java Spring, ASP.NET, Ruby • Docker, Kubernetes, AWS, Nginx, Linux • CI/CD pipelines, monitoring, logging systems • From MVP to enterprise-level traffic without rewriting the system later. 🧠 AI-Integrated Software Systems AI functions as an infrastructure layer inside modern applications. Experience includes: • NLP, OCR, facial and speech recognition • Intelligent search systems with vector databases • RAG pipelines and knowledge systems • Multi-model orchestration systems • GPU-optimized inference pipelines Frameworks and tools: • PyTorch, TensorFlow, Keras, scikit-learn • Whisper, Tesseract, PaddleOCR • DeepFace, InsightFace • Elasticsearch, Pinecone • CUDA, cuDNN Focus areas: performance, cost efficiency, production readiness, scalability. ⚡ Backend Engineering • RESTful APIs and GraphQL • Event-driven systems • Queue-based processing • Background job orchestration • Secure authentication and authorization Databases: • PostgreSQL, MySQL, MongoDB • Query optimization, indexing, full-text and vector search Databases and Optimization • PostgreSQL, MySQL, and MongoDB • Query optimization, indexing strategies, and search systems 🎯 Frontend Engineering • React, Next.js, Vue, Nuxt, Angular • SEO optimization • Performance tuning • Lazy loading and caching strategies • Responsive and scalable UI architecture 🌐 Real-Time Systems • WebRTC, MQTT, Socket • Streaming systems • Telecom systems Designed for low latency, high concurrency, and production reliability. 📱 Cross-Platform Development • Flutter • React Native • Native Android • Firebase ecosystem 🌟 Professional Approach • Systems thinking mindset • Scalability-focused architecture • Long-term maintainability • Clear communication • Reliable delivery 🌟 Why Clients Hire Me Not because I list technologies. But because I understand: • Business logic • Scalability constraints • Infrastructure costs • Security risks • Long-term maintainability I think like a technical founder or CTO. I don’t just build features. I design systems that support growth. 📈 Let’s Build It the Right Way If you need: • A SaaS platform built from scratch • A scalable enterprise backend • AI integrated into your product • A system redesign for performance • An architecture that can scale without limits Let’s build it properly from day one. Because great software isn’t just written. It’s engineered.