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I help companies design and build applied AI solutions and automation that solve concrete business problems — reliably, pragmatically, and without hype. 🇩🇪 I frequently work with German-speaking companies across DACH (Germany, Austria, Switzerland), and also collaborate with international teams and startups. My focus is on AI systems that work in real-world environments, not demos or hype projects. ⚡ What I Build & Deliver • Applied AI solutions for real business processes • AI prototypes and MVPs to validate ideas fast • Computer vision systems (detection, extraction, measurement) • Document and data extraction from images, PDFs and structured files • AI-driven automation and workflow optimization • Web-based tools and dashboards to make AI usable for teams 🏗️ How I Work • Clear scoping and honest feasibility assessment • Pragmatic solutions instead of over-engineering • Focus on maintainability, data quality and real-world constraints • Transparent communication and structured execution • From prototype to production-ready architecture 🎓 Background I combine a strong academic background in Artificial Intelligence (MSc) with hands-on software engineering experience. I’ve worked on applied AI systems spanning automation, computer vision and machine learning in real operational contexts. 🚀 Have an AI idea you want to validate or bring into production? Let’s discuss your use case and define a clear, realistic next step.

5⭐ 𝗖𝗹𝗶𝗲𝗻𝘁 𝗥𝗲𝘃𝗶𝗲𝘄: "Highly recommended! Vivek is professional, responsive, and delivers excellent work. He quickly understood my requirements, communicated clearly throughout the project..." 🎓 𝗠𝗮𝘀𝘁𝗲𝗿'𝘀 𝗶𝗻 𝗘𝗺𝗯𝗲𝗱𝗱𝗲𝗱 𝗦𝘆𝘀𝘁𝗲𝗺𝘀 + 𝟳 𝘆𝗲𝗮𝗿𝘀' 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 | Python, OCR, n8n, OpenAI, Claude, Computer Vision Top Rated Plus AI automation engineer helping businesses turn messy documents and manual workflows into reliable automation systems using n8n, OCR, Python, OpenAI/Claude, RAG, and computer vision. I build AI systems that extract structured data from PDFs, invoices, receipts, emails, forms, scanned documents, and images — then automate the workflow into CRMs, spreadsheets, databases, or approval systems. 👉 Proof from past work: • Cut image-processing time by 94% for Magna International: 37s to 2.5s • Built n8n workflows and RAG agents saving a client 20+ hours/week • Delivered AI workflows clients described as precise, efficient, and fully aligned with requirements • Built YOLO + Python real-time sports analytics for player and ball tracking 👉 What I build: • AI data extraction from invoices, PDFs, forms, receipts, shipping labels, images, and scanned documents • n8n automations connecting Gmail, Google Sheets, Airtable, CRMs, APIs, databases, webhooks, and human review steps • Python/FastAPI backends for workflows that need more reliability than a no-code automation • OCR and document AI pipelines using OpenAI, Claude, Mistral OCR, Tesseract, RAG, vector databases, and validation logic • AI agents for classification, routing, summarization, field extraction, exception handling, and decision support • Computer vision pipelines with OpenCV, YOLO, PyTorch, TensorFlow, and real-time image/video processing 👉 Where I bring the most value: ✅ AI Automation Engineering • n8n, Python, OpenAI/Claude APIs, webhooks, and REST API integrations • Production-grade error handling, retry logic, monitoring, and human-in-the-loop review • Workflow automation for Gmail, Google Sheets, Airtable, CRMs, databases, and internal tools • Python/FastAPI backends when an automation needs more reliability than a no-code workflow ✅ AI Data Extraction & Document Processing • OCR + AI data extraction for invoices, PDFs, receipts, forms, shipping labels, and scanned documents • Document classification, field extraction, validation, and exception routing • RAG workflows for searching, comparing, and summarizing internal documents • n8n automations that move extracted data into Sheets, CRMs, databases, APIs, or approval queues ✅ GDPR-Aware Automation for EU Businesses • GDPR-aware AI automation for European teams handling sensitive documents or customer data • Privacy-conscious workflows with human review, audit trails, access control, and data-minimization thinking • On-premise or self-hosted options where documents should not be sent through unnecessary third-party tools • Clear handoff documentation so your team understands where data goes, what is stored, and what can be deleted ✅ Computer Vision & Python Automation • Computer vision pipelines with OpenCV, YOLO, PyTorch, TensorFlow, and image processing • Real-time object detection, tracking, video analytics, and quality-control workflows • Performance optimization for production systems, including latency and processing-speed improvements • Dockerized deployment, clean handoff, and documented production-ready code ✅ AI Agents & Workflow Intelligence • AI agents for classification, routing, summarization, decision support, and task automation • LLM-powered workflows using OpenAI, Claude, RAG, vector databases, and prompt optimization • Automation rescue: fixing broken n8n workflows, unreliable OCR pipelines, and fragile scripts • Long-term automation support, improvements, and 30-day post-deployment warranty Tech Stack: n8n, Python, FastAPI, Flask, OpenAI API, Claude API, RAG, AI agents, prompt engineering, webhooks, REST APIs, SQL, PostgreSQL, Docker, AWS, Google Sheets, Gmail, Airtable, CRMs, Slack, Notion, Mistral OCR, Tesseract, PDF extraction, OpenCV, YOLO, PyTorch, TensorFlow. I’m strongest when the workflow is messy: inconsistent PDFs, poor image quality, missing fields, vendor-specific formats, manual checks, broken n8n workflows, or automations that fail when real-world edge cases appear. You get rapid prototypes, production-ready code, Dockerized deployment, clear documentation, and a 30-day post-deployment warranty for issues after handoff. Send me the workflow, one sample document, or your current broken automation. I’ll outline the shortest reliable path to automate it.

I'm a Machine Learning Engineer and Python Developer with 4+ years of hands-on experience solving real-world problems using advanced AI. I specialize in deploying cutting-edge ML/AI solutions that enhance decision-making, boost operational efficiency, and reduce costs. My background includes working with startups and tech companies on projects involving: ✅ Language Modeling & LLMs (GPT, BERT, LLaMA, Mistral) ✅ Generative AI (Stable Diffusion + LoRA, DCGAN) ✅ Conversational AI using LangChain, OpenAI, and custom chatbot solutions ✅ Computer Vision (Image Classification, Object Detection/Tracking with YOLO + OpenCV) ✅ Data Annotation & Labeling using Roboflow and Label Studio ✅ Speech Technologies (Text-to-Speech & Speech-to-Text) ✅ Web Scraping & Automation using Python ✅ Full-stack app development with Django, Flask, FAST API, and PostgreSQL Key Skills: LangChain · OpenCV · OpenAI · YOLO · Hugging Face · Text Classification · Text to Speech (TTS) · Speech to Text (STT) · GPT · Image Classification · Chatbots · RNN · CNN · DCGAN · Fastai · Transformers · LLMs · NLP · TensorFlow · Keras · PyTorch · Django · PostgreSQL · Web Scraping · Python Automation · FAST API · Flask · Roboflow · Label Studio Let’s collaborate to elevate your AI initiatives to new heights!

A Data Scientist and Technical Writer based in Vienna, Austria, with extensive experience in Data Science, Machine Learning, Deep Learning, and Generative AI (GenAI) applications. My Technology Stack: Programming Languages: Python, R, MATLAB, JavaScript, C/C++, C# Machine Learning Libraries and Frameworks: Scikit-learn, TensorFlow, PyTorch Data Visualization Tools: Tableau, Google Data Studio, D3.js, Plotly, Matplotlib, Bokeh, ggplot2 Operating Systems: Windows, Linux (Ubuntu) Database Management Systems: PostgreSQL, MongoDB, MySQL, SQL Server, Vector databases (Milvus, Weaviate, Pinecone) Version Control, Containerization & Cloud Services: Git, AWS, Docker If you’re working on projects related to Data Science or Machine Learning and need assistance, feel free to reach out—I’d be happy to collaborate and contribute to your success!

My focus is simple: stop building static tools. Start shipping intelligent, autonomous AI systems that drive real business results. With 40+ years of combined engineering experience and 870+ completed projects, I work as a Machine Learning Engineer, AI Engineer, MLOps Engineer, and Python Developer - delivering production-grade AI systems using Python, LangChain, LangGraph, RAG pipelines, LLM integrations, and full MLOps / DevOps infrastructure. I operate with a team of 90+ engineers across AI, Backend, and DevOps, serving US and European clients from prototype to production. Across 870+ projects and 40+ years of combined stack experience, our team has scaled AI systems to handle millions of requests daily - from RAG pipelines that replaced 3 full-time support agents, to LLM workflows that cut manual operations by 70%, to MLOps infrastructure that grew deployments from 1 to 120 per month. With 870+ projects behind us, I deliver end-to-end LLM integration using Python, GPT-4, GPT-5, Claude, LLaMA, and Mistral - including prompt engineering, context engineering, and embedding pipelines. Using LangChain and LangGraph, I build multi-agent AI systems where each agent handles retrieval, reasoning, and execution autonomously. Across 40+ years of combined AI development experience, we've shipped agent orchestration systems for fintech, healthcare, SaaS, and enterprise clients. I build RAG pipelines using Python, Weaviate, Chroma, semantic search, and knowledge retrieval systems integrated into production workflows - connected to PostgreSQL, MongoDB, CRMs, and internal knowledge bases. With 870+ completed projects, including dozens of RAG systems, one pipeline alone reduced support workload equivalent to 3 full-time employees, cutting response time from hours to seconds. Named Entity Recognition, text classification, semantic search, multilingual NLP, question-answering, sentiment analysis, and topic modeling - using Python, BERT, FastAPI, and modern LLM approaches. With 40+ years of engineering experience across NLP and AI stacks, I combine classical ML with cutting-edge LLM technology for production-ready language systems. I design, deploy, and scale AI systems in production using Kubernetes, Docker, Terraform, Ansible, Jenkins, Kafka, RabbitMQ, Grafana, Prometheus, and Nginx across AWS, GCP, and Azure. Across 870+ delivered projects, deployments have scaled from 1 per month to 120 per month, deployment time decreased by 85%, and infrastructure costs were reduced by 55%. With 40+ years of combined DevOps and AI infrastructure experience - I don't just build models, I deploy, monitor, optimize, and scale them. Across 870+ completed projects with our 90+ engineer team, we've built and deployed Python-based LLM and RAG systems for Fintech (fraud detection, automated KYC, financial intelligence), Healthcare (HIPAA-compliant AI pipelines, patient data retrieval, clinical NLP), SaaS (AI copilots, agent workflows, automated onboarding), and Enterprise (internal knowledge bases, document intelligence, multi-agent orchestration with LangGraph and n8n). With 40+ years of cross-industry AI experience, we align every Python, FastAPI, Kafka, and Kubernetes decision to your business outcome not just the tech spec. 🔥 85+ completed projects (40+ SaaS & MVP platforms) delivered as a Full Stack Developer & React Developer 💰 Startup MVP platforms generated $500K+ revenue in their first 6 months 👥 SaaS products supporting 10K–50K active users built by an expert Full Stack Developer 📈 One platform grew from 2K to 7K users through continuous product updates by a Web Developer ⚡ Backend systems processing 300K–500K A 📍 Core tech stack PythonLangChainLangGraphRAG pipelinesGPT-4 / GPT-5ClaudeLLaMA MistralBERT NLPFastAPI DjangoPostgreSQL MongoDB RedisWeaviate ChromaKubernetes Docker TerraformAWS GCP AzureKafka RabbitMQ n8nGrafana Prometheus NginxJenkins Ansible Terraform Send me a message with your idea or current setup whether it's a RAG pipeline, an LLM agent built with LangChain or LangGraph, a Python backend on FastAPI, or a full MLOps infrastructure on AWS, GCP, or Azure with Kubernetes and Docker. With 870+ projects completed and 40+ years of combined experience across Python, LLM, RAG, NLP, Kafka, Postgres, and n8n we move fast, take full ownership, and ship AI systems that work in production from day one. 👋 Whether as Python Full Stack Developer to ship a production-grade web app, a Python Developer AWS to deploy scalable microservices, a Python Full Stack Developer Flask expert to build modern backend-driven applications, or a Python AI Developer to wire up intelligent automations I deliver clean, reliable, maintainable solutions that solve real problems. If you're also searching for a solid web developer, full-stack developer I bring the same professional skills 📩 Send me a message with your current setup - I'll tell you what's missing, what can be improved, and whether your AI system is ready for production.

⏩ More than 5y experience in Python, ML and data science in academia and industry, coupled with a commitment to staying up-to-date ⏩ Convinced that comprehensive communication is key to ideally complete your project, just as delivering clean, well-documented code ensures long-term maintainability ⏩ PhD in machine learning for cybersecurity, so I can build your ML stack and ensure its secure deployment I love working on challenging tasks. My broad interest in ML techniques allows me to pick the right method for any task and my mathematical understanding allows me to put ideas from cutting-edge research into practice. From building your data lake, over designing a custom neural network that suits your data best, to ensuring its scalable Cloud-based or on-prem deployment, I am well-prepared to delivering impactful results. 𝗙𝗿𝗲𝗾𝘂𝗲𝗻𝘁𝗹𝘆 𝗨𝘀𝗲𝗱 𝗧𝗼𝗼𝗹𝘀 • Python, C++ • Keras, Jax, tensorflow, PyTorch, HF Transformers for 🧠 Deep Learning • AWS Sagemaker AI, Firehose, Athena, S3, Lambdas for ☁️ Cloud-based data (pre)processing and model deployment • scikit-learn, pandas, SciPy, XGBoost, pyod, matplotlib, seaborn for 📊 data mining & visualization • librosa, pyaudio, pyroomacoustics, madmom for 🎶 audio ML tasks • OpenCV, PaddleOCR, YOLO for 🎨 CV tasks • LlamaIndex, LangChain for RAG • GitHub Actions, Docker containerization, Amazon ECR for MLOps • FastAPI, flask, nginx, MySQL/Postgres web backend stack • GCE, AWS EC2 and CUDO Compute for 🖥️ Cloud VMs/GPUs • Terraform for IaC 𝗦𝗲𝗹𝗲𝗰𝘁𝗲𝗱 𝗣𝗿𝗼𝗷𝗲𝗰𝘁𝘀 👉 𝘐𝘯 𝘾𝙤𝙢𝙥𝙪𝙩𝙚𝙧 𝙑𝙞𝙨𝙞𝙤𝙣, 𝘐 𝘪𝘮𝘱𝘭𝘦𝘮𝘦𝘯𝘵𝘦𝘥 • a full OCR pipeline with subsequent PDF data extraction, based on the Differentiable Binarization model for text detection, the PARSeq ViT model for text recognition and transformers using multidimensional RoPEs • image segmentation with BASNet. • object detection, classification and segmentation based on the Mask RCNN architecture. 👉 𝘐𝘯 𝘵𝘩𝘦 𝘤𝘰𝘯𝘵𝘦𝘹𝘵 𝘰𝘧 𝙩𝙧𝙖𝙣𝙨𝙛𝙤𝙧𝙢𝙚𝙧𝙨, I engineered highly optimized custom layer implementations in C++/CUDA, including both forward pass and manual gradient backpropagation. 👉 𝘍𝘰𝘳 𝙡𝙖𝙧𝙜𝙚-𝙨𝙘𝙖𝙡𝙚 𝙙𝙖𝙩𝙖 𝙚𝙣𝙜𝙞𝙣𝙚𝙚𝙧𝙞𝙣𝙜, 𝘐 𝘥𝘦𝘷𝘦𝘭𝘰𝘱𝘦𝘥 a scalable data lake solution based on Terraform-deployed AWS services, leveraging Amazon Firehose, Amazon S3 and AWS Lambdas for data ingestion, Amazon EventBridge for real-time event propagation and Amazon Athena and FastAPI for query and endpoint development. 👉 𝘐𝘯 𝙘𝙮𝙗𝙚𝙧𝙨𝙚𝙘𝙪𝙧𝙞𝙩𝙮, I conducted comprehensive data analysis, algorithm development and ML model design in the context of network traffic analysis during my PhD journey. 👉 𝘐𝘯 𝙖𝙪𝙙𝙞𝙤 𝙈𝙇, 𝘐 • led research on generative audio ML, testing various architectures. • performed MIR model implementation and improvements for a major Austrian startup. 👉 𝘐𝘯 𝘴𝘮𝘢𝘭𝘭𝘦𝘳 𝘱𝘳𝘰𝘫𝘦𝘤𝘵𝘴, 𝘐 𝘢𝘭𝘴𝘰 𝘤𝘰𝘯𝘵𝘳𝘪𝘣𝘶𝘵𝘦𝘥 𝘵𝘰, 𝘦.𝘨., • VAEs in the context of molecule discovery. • GANs for image generation. 𝗠𝘆 𝗕𝗮𝗰𝗸𝗴𝗿𝗼𝘂𝗻𝗱 • Education in electrical engineering, which gives me a strong theoretical underpinning • Extensive writing experience as evidenced by more than 10 academic papers, several authored grant applications and a doctoral thesis nominated for the Austrian national Zemanek prize • Used various deep learning techniques including RNNs, CNNs, MLPs, transformers throughout previous work • Deployed various ML and data mining techniques including 𝘬NN, XGBoost, Random Forests, clustering and anomaly/outlier detection in previous projects • Azure Cloud Certification 𝘓𝘦𝘵'𝘴 𝘣𝘶𝘪𝘭𝘥 𝘴𝘰𝘮𝘦𝘵𝘩𝘪𝘯𝘨 𝘨𝘳𝘦𝘢𝘵 𝘵𝘰𝘨𝘦𝘵𝘩𝘦𝘳.