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I build AI products for startup founders. Custom platforms that run in production and serve or scale a real business. WHO I WORK WITH Founders building a new AI product. Owners starting an AI line inside an existing business. You're building something that doesn't exist yet. WHAT I BUILD • AI products and platforms, architecture to launch • Multi-agent systems that run unattended • Automation platforms written in code, not stitched together in Zapier • RAG and LLM pipelines on real business data • Rebuilds of AI projects that stalled before production HOW FOUNDERS USUALLY FIND ME A prototype worked in the demo and broke on real data. Or a developer left something half-built. Either way the fix is the same: a foundation that holds. I'll tell you what's worth building before I build it. Sometimes that means talking you out of something. Most projects average around $10k and run for months, not days.

🔥 𝗦𝗲𝗻𝗶𝗼𝗿 𝗔𝗜/𝗠𝗟 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁 | 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝘁𝗶𝘀𝘁 | 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 | 𝗚𝗼𝗼𝗴𝗹𝗲 𝗖𝗹𝗼𝘂𝗱 𝗣𝗿𝗲𝗺𝗶𝗲𝗿 𝗣𝗮𝗿𝘁𝗻𝗲𝗿 | 𝟭𝟬+ 𝘆𝗲𝗮𝗿𝘀 𝗼𝗳 𝗲𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 🔥 A highly accomplished and results-driven AI/ML Architect with over 10 years of experience, specializing in architecting and deploying advanced AI/ML solutions for enterprise clients across diverse industries including airline, automotive, marketing analytics, political outreach, and fact-checking for publishers. My background spans the entire AI/ML lifecycle, from strategic solution design to hands-on implementation and operationalization of scalable, real-world systems. I'm currently leading the team at AI Arch Solutions to excel at translating complex business challenges into innovative, AI-driven solutions that deliver measurable ROI. 💪 𝐂𝐎𝐑𝐄 𝐂𝐎𝐌𝐏𝐄𝐓𝐄𝐍𝐂𝐈𝐄𝐒 💪 𝘼𝒈𝙚𝒏𝙩𝒊𝙘 𝘼𝑰 & 𝑨𝙪𝒕𝙤𝒏𝙤𝒎𝙤𝒖𝙨 𝙎𝒚𝙨𝒕𝙚𝒎𝙨 ● 𝗔𝗴𝗲𝗻𝘁 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲𝘀: ReAct (Reasoning and Acting), RAG (Retrieval-Augmented Generation), Multi-Agent Systems (MAS), Hierarchical Agent Architectures (e.g., Manager-Worker) ● 𝗖𝗼𝗿𝗲 𝗔𝗴𝗲𝗻𝘁 𝗔𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀: Tool Use & Function Calling, Complex Task Decomposition, Dynamic Planning & Reasoning, Self-Correction & Reflection Loops (e.g., Reflexion) ● 𝗠𝗲𝗺𝗼𝗿𝘆 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁: Designing and implementing agent memory systems, including short-term (context window), long-term (vector databases), and structured memory approaches ● 𝗣𝗿𝗼𝗺𝗽𝘁 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 & 𝗦𝘁𝗮𝘁𝗲 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁: Advanced prompt chaining, state tracking across multi-turn interactions, and managing conversational context for complex tasks 𝑫𝙖𝒕𝙖 𝙎𝒄𝙞𝒆𝙣𝒄𝙚 & 𝘿𝒂𝙩𝒂 𝑬𝙣𝒈𝙞𝒏𝙚𝒆𝙧𝒊𝙣𝒈 ● 𝗠𝗼𝗱𝗲𝗹 𝗣𝗿𝗲𝗽𝗮𝗿𝗮𝘁𝗶𝗼𝗻: Data cleaning, data imputation, feature engineering, feature space reduction (PCA) ● 𝗠𝗼𝗱𝗲𝗹 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲: LLMs, Neural Networks, NLP (BERT, ELMO, GPT Variants), K-Means / Hierarchical Clustering, Logistic Regression, Random Forest (XGBoost), K-Nearest Neighbor, Naïve Bayes, GridSearch, Causal Inference, Bayesian Marketing Mix Modeling ● 𝗗𝗮𝘁𝗮 𝗩𝗶𝘀𝘂𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻𝘀: Tableau, Seaborn, Matplotlib, Plotly, Dash ● 𝗖𝗼𝗱𝗶𝗻𝗴: Python (NumPy, pandas, scikit-learn, TensorFlow, Keras, NLTK, LangChain, Streamlit), SQL, Java, R ● 𝗗𝗮𝘁𝗮 𝗧𝗼𝗼𝗹𝘀: Google Cloud Platform (BigQuery, Vertex AI), AWS (SageMaker, Lambda, S3), Databricks, Airflow (DAGs), Pinecone, PostgreSQL ● 𝗘𝘅𝗽𝗲𝗿𝗶𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻: Regression Discontinuity Design, Interrupted Time Series, A / B Testing

Hi, I am an AI and Full-Stack Engineer with over ten years of experience designing and building intelligent, scalable, and production-ready software systems. I help startups and growing businesses turn complex problems into simple, smart, and automated solutions. My goal is always to save time, improve decision-making, and create applications that scale effortlessly. I specialize in Python with frameworks like Django, FastAPI, and Flask for backend development. I write clean, maintainable code with a focus on performance, reliability, and scalability. I also work with React and Next.js to deliver smooth and responsive user interfaces. Alongside full-stack development, I specialize in natural language processing and Generative AI. I build applications using large language models, LangChain, and LlamaIndex. I develop retrieval-augmented generation systems, conversational AI, semantic search, knowledge base automation tools, and other AI-powered solutions that turn data into insight and workflows into intelligent automation. I have hands-on experience with transformer models such as GPT, LLaMA, Mistral, Claude, Gemini, and Qwen. I integrate them using fine-tuning, prompt engineering, embeddings, and custom API pipelines. I work with vector databases like Pinecone, Weaviate, FAISS, and ChromaDB to enable context-aware intelligence and fast data retrieval. I have delivered end-to-end solutions including AI-powered SaaS platforms, custom dashboards, automation systems, and text-to-SQL tools. I focus on strong backend architecture, intelligent AI logic, and seamless user experiences. I also have experience deploying applications on cloud platforms such as AWS, GCP, and Azure using Docker and CI/CD pipelines to ensure reliability and scalability. 𝗖𝗼𝗿𝗲 𝗦𝗸𝗶𝗹𝗹𝘀 𝗮𝗻𝗱 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝗶𝗲𝘀: Python • Django • FastAPI • Flask • React • Next.js NLP • LLMs • RAG Systems • Semantic Search • Summarization • NER • Sentiment Analysis Generative AI • GPT • Claude • LLaMA • Gemini • Qwen • Hugging Face • Transformers Vector Databases: Pinecone, Weaviate, FAISS, ChromaDB Prompt Engineering • Embeddings • Document AI • Data Processing & Automation Cloud Deployment & SaaS Solutions (AWS, GCP, Azure) 💬I treat every project like it’s my own, with care, precision, and a focus on real results. I will bring experience, skill, and care to your project. I will work with you to create solutions that are intelligent, reliable, and built to last. Let us build something remarkable together.

𝐁𝐚𝐜𝐤𝐠𝐫𝐨𝐮𝐧𝐝: PhD in Theoretical Computer Science; ex-Director of ML Research at Nuro; ex-Chief Scientist at Huawei Research; 45 publications and 40 patents; area chair and reviewer at CVPR, NeurIPS, ICML, and ICLR. I've led teams of 25, but what I love is building - which is why I'm here: full-time, hands-on, writing the code myself. I build ML systems that make it to production. If your RAG pipeline hallucinates, your agents loop and burn tokens, your fine-tune won't converge, or accuracy has plateaued and nobody knows why - that's the work I do best. 𝟐𝟎 𝐲𝐞𝐚𝐫𝐬 from DSP firmware to frontier multimodal AI means I debug these systems from silicon up, not by guessing. 𝐖𝐡𝐚𝐭 𝐈 𝐁𝐮𝐢𝐥𝐝 ➤ Agentic AI: multi-agent workflows with LangGraph and OpenAI/Anthropic agent stacks - tool design, custom MCP servers, memory, guardrails, LLM-as-judge validation loops. Agents that finish the job, reliably and at predictable cost. ➤ Computer vision at extreme scale: face recognition deployed globally at Huawei; gigapixel pathology imaging; video retrieval (MDMMT, top of its benchmark); super-resolution, edge compression. ➤ RAG & LLM applications: retrieval that actually grounds its answers; multimodal RAG with Vision-Language Models (SafeAuto, ICML 2025); evaluation harnesses so quality is measured, not assumed. ➤ LLM fine-tuning & optimization: LoRA/QLoRA, quantization, distillation, synthetic data pipelines. Frontier-model quality at a cost you can afford to run. ➤ Backend & MLOps: Python/FastAPI microservices, REST APIs, Docker, CI/CD, model serving (vLLM, Triton), Postgres/Redis, vector DBs, AWS/GCP - on a systems background that goes down to flash controllers, LDPC error-correcting codes, and DSP firmware (30+ patents at LSI/Broadcom). ➤ Data science & classic ML: credit scoring, churn prediction, fraud/anomaly detection, forecasting, recommenders, A/B testing - shipped as VP of R&D at a FinTech holding. ➤ AI reliability & safety: adversarial robustness (I authored AdvHat, the widely cited real-world attack on ArcFace FaceID), certified defenses, uncertainty quantification, safe RL. I know exactly how models fail and build guardrails that hold. 𝗥𝗲𝗰𝗲𝗻𝘁 𝗣𝗿𝗼𝗷𝗲𝗰𝘁𝘀 𝗜’𝗺 𝗣𝗿𝗼𝘂𝗱 𝗢𝗳: 🏆 FinTech: as VP of R&D, built an agentic underwriting platform - LangGraph agents with custom MCP tools that read financial documents (OCR + VLM) and draft credit decisions. Manual review time dropped ~70%, and fraud recall went up 18 points without raising false positives. 🏆 Healthcare: gigapixel pathology scans, billions of pixels each. Multi-scale transformers plus an LLM that drafts the structured findings. Pathologists spend ~40% less time per case; distillation cut inference cost 5x. 🏆 Autonomous driving: prediction, diffusion-based planning, and RL motion selection at Nuro and Gatik - top places on Argoverse and Apolloscape, and SafeAuto (ICML 2025) is SOTA on driving benchmarks. 𝐖𝐡𝐞𝐫𝐞 𝐈'𝐯𝐞 𝐖𝐨𝐫𝐤𝐞𝐝 🌐 Now: VP / Head of R&D at a FinTech holding; Adjunct Professor of ML and AI at Sofia University (Palo Alto) 🌐 Head of AI at Logical Intelligence 🌐 Sr. Director of AI Research at Gatik (Silicon Valley) 🌐 Director of ML Research at Nuro (Silicon Valley) 🌐 Chief Scientist at Huawei Research 🌐 Managing Director at the Artificial Intelligence Research Institute 🌐 Senior Software Engineer at LSI (now Broadcom) - 6 years fully remote for a US company Remote, hybrid, or embedded - I've delivered in all three. 📌 I've usually already solved the harder version of your problem. I measure before I claim: every engagement ships with evaluation you can rerun yourself. Your team keeps the knowledge - I founded Nuro ML University (100+ engineers trained) and teach as I build. And I've been graded on delivery, not just papers: 𝟏𝟑 𝐜𝐨𝐫𝐩𝐨𝐫𝐚𝐭𝐞 𝐚𝐰𝐚𝐫𝐝𝐬 at 𝐇𝐮𝐚𝐰𝐞𝐢, including Excellent Delivery and Customer Success; 𝐢𝐧𝐯𝐢𝐭𝐞𝐝 𝐬𝐩𝐞𝐚𝐤𝐞𝐫 at 𝐂𝐕𝐏𝐑, 𝐀𝐀𝐀𝐈, and 𝐖𝐀𝐂𝐕 𝐰𝐨𝐫𝐤𝐬𝐡𝐨𝐩𝐬 in 2025. Short technical discovery, architecture and milestone plan, a working system early, iteration against agreed metrics (accuracy, latency, cost), then documentation and a recorded handoff. Plain-English updates, async-friendly, US and EU hours. Stack: Python, PyTorch, C++, CUDA, FastAPI, OpenAI/Anthropic APIs, LangChain/LangGraph, MCP, vLLM, Transformers, RAG, NLP, FAISS/Pinecone/Weaviate, LoRA/QLoRA, diffusion models, RL, scikit-learn, XGBoost, Docker, AWS/GCP, W&B, MLflow. Not ready for a full build? Start with a fixed-scope audit of your RAG, agent, or ML system - architecture review, evaluation gaps, and a prioritized fix list you can execute with or without me. Send me the problem - what you're building, what's failing, what "good" looks like - and I'll reply with a concrete technical assessment and a scoped plan within one business day. Alex

Senior AI/ML Architect with 20+ years delivering measurable results. For the past few years, all work has been built with Claude Code, with deep hands-on experience in Claude API, MCP servers, agent design, and AI workflow automation. I also coach teams and founders on how to adopt these tools in their day-to-day work, from prompt design to building production-ready automations. Available for AI enablement, 1-on-1 coaching, team training, automation design, and strategic AI leadership roles. Accomplished scalable AI solutions as measured by founding Mission Automate and leading teams at Chatsi AI by architecting end-to-end platforms with Python, TensorFlow, PyTorch, and cloud ML services. Accomplished revenue-driving features as measured by developing systems generating millions in sales (VitalSource) and serving millions of users (Charles Schwab) by building full-stack solutions with Ruby, JavaScript, and optimized database architectures. Accomplished cross-industry impact as measured by successful deployments in fintech, e-commerce, healthcare, and education by leveraging AI/ML expertise (OpenCV, Transformers, OpenAI) with Agile methodologies and cloud platforms (AWS, GCP, Azure). Core Stack: Claude Code, Claude API, MCP, n8n, Zapier, Python, Ruby, AI/ML (TensorFlow, PyTorch), Cloud Platforms, Kubernetes, PostgreSQL/MongoDB What I'm proud of: • Live Claude Code demos at Mindstone AI Meetup, Silicon Valley (2026) • Mission Automate featured by Amazon SageMaker • Published StyleGAN2-ADA superhero generation research • Speaker at RailsConf 2021

Expert Vetted. Stanford MS in AI. 200+ projects. 100% success rate. $1M+ delivered through Upwork. If you are building AI Agents, automating business workflows, deploying LLMs, or scaling machine learning systems, you have found the right engineer. I'm Tayyab. 10 years building production-grade AI for startups, scale-ups, and enterprises across legal, healthcare, finance, insurance, and SaaS. My work has helped clients raise $50M in funding, cut processing time by 40%, achieve 90% prediction accuracy, scale deal flow by 10x, and eliminate hundreds of hours of manual work annually. 🤖 AI Agents & Workflow Automation ▸ Multi-agent orchestration: LangGraph, CrewAI, AutoGen, OpenAI Agents SDK, Semantic Kernel ▸ n8n, Make, Zapier, Pipedream: end-to-end business process automation ▸ CRM, email, document, and reporting automation: Salesforce, HubSpot, Slack, Notion, Google Workspace ▸ Celery, Redis, Temporal: distributed workflow execution ▸ Human-in-the-loop systems, agent memory, tool use, approval workflows 🧠 Generative AI, LLMs & RAG ▸ GPT-4o/o1/o3, Claude 3.5, Gemini, Llama 3, Mistral, Qwen, HuggingFace, Groq, Ollama ▸ Enterprise RAG: Pinecone, Qdrant, Weaviate, ChromaDB, FAISS, pgvector, Neo4j ▸ Fine-tuning: QLoRA, DeepSpeed, Unsloth, LoRA on GPU clusters ▸ LangChain, LlamaIndex, LangSmith, DSPy, TextGrad, MemGPT 📊 Machine Learning & Computer Vision ▸ PyTorch, TensorFlow, Scikit-learn, XGBoost, LightGBM: classification, regression, forecasting, anomaly detection ▸ YOLO, Detectron2, OpenCV, OCR: document intelligence and visual AI ▸ Voice AI: Whisper, ElevenLabs, Retell AI, Bland AI, Twilio, LiveKit ▸ Stable Diffusion, Flux, ComfyUI: generative imaging and video ☁️ MLOps & Cloud ▸ AWS, GCP, Azure: Kubernetes, Docker, serverless ▸ MLflow, BentoML, Weights & Biases: model deployment and monitoring ▸ FastAPI, Flask, Node.js, React, PostgreSQL, MongoDB 🏆 Selected Projects ▸ Enterprise cloud cost intelligence platform: 25% cost reduction, $50M funding secured ▸ Insurance medical records pipeline: 40% faster processing, 90% cost prediction accuracy ▸ RAG-powered legal analysis system: 80% alignment with real judicial verdicts ▸ NLP contract intelligence platform: 4 hours saved per contract, 80% accuracy improvement ▸ Sustainability analytics dashboard: 130M+ tons of CO2e managed, 200+ hours saved annually ▸ ML startup evaluation engine: 10x deal flow capacity, weeks to seconds per evaluation ▸ Multi-agent lead generation system: 70% reduction in manual prospecting effort ▸ AI conversational support system: thousands of daily conversations automated across multiple channels ✅ Why Me? ▸ Stanford MS in AI: Top 1% Expert Vetted on Upwork ▸ 200+ projects, zero failed engagements, $1M+ delivered ▸ Systems that run in production, not demos that die in staging 📩 AI Agents, workflow automation, LLMs, or machine learning: let's talk. Machine Learning, Deep Learning, Generative AI, LLMs, AI Agents, Agentic AI, Multi-Agent Systems, Workflow Automation, AI Automation, LangChain, LangGraph, CrewAI, AutoGen, RAG, Retrieval-Augmented Generation, Vector Databases, Pinecone, Weaviate, FAISS, Fine-Tuning, QLoRA, Prompt Engineering, OpenAI, GPT-4, Claude, Gemini, Llama, Mistral, HuggingFace, PyTorch, TensorFlow, XGBoost, LSTM, Transformers, YOLO, OpenCV, OCR, Stable Diffusion, Voice AI, Whisper, ElevenLabs, n8n, Make, Zapier, FastAPI, Docker, Kubernetes, AWS, GCP, Azure, MLflow, MLOps, Time Series Forecasting, Anomaly Detection, Semantic Search, Neo4j, pgvector, Elasticsearch