Hire the Best Google AutoML Freelancers in Lahore, PK

Available Now I'm an AI data annotator with hands-on experience in computer vision data labeling for machine learning teams. I work inside CVAT, Labelbox, Roboflow, and Label Studio daily, handling everything from image annotation and video annotation to complex segmentation tasks — so your engineers can focus on the model, not the data. My work covers the full range of computer vision annotation: bounding box annotation for object detection, semantic segmentation and instance segmentation masks, polygon annotation for irregular shapes, keypoint labeling for pose estimation, and frame-by-frame object tracking in video datasets. Each label follows your guidelines exactly — and when I hit an edge case, I flag it instead of guessing. I support machine learning and AI development teams who need clean, consistent training data at scale. Whether you have 500 images or 500,000, the quality standard stays the same — because one bad label in a batch affects everything downstream. ✅ What I bring to every project: 🔹Pixel-accurate segmentation masks with no sloppy edges 🔹Consistent bounding boxes across large object detection datasets 🔹Reliable video annotation with proper object tracking between frames 🔹Fast turnaround with clear communication at every stage 🔹A annotator who reads the labeling guide before touching the first image ➡️ Let’s Work Together Send me your dataset, annotation guidelines, or a sample task. I'll return a labeled batch so you can judge the quality yourself before committing to a full project.

I WORK ONLY IN EASTERN HOURS, AND OPEN TO FT ROLES My expertise include, → Frontend: REACT, Redux, Angular, Javascript, Typescript, HTML, CSS, Bootstrap, MUI → Backend: Nodejs, Parse Server, Supabase, Python Django → Database: MongoDB, Neo4j, postgres, Firebase realtime database → Websockets: NATS (a super fast infrastructure that allows large data exchange, segmented in the form of messages through websockets) → REST API development and integrations: Stripe, AssemblyAI, OpenAI, Google, Twilio, MemGPT, Autogen, Sendgrid, Mailgun, Zoom → Data Visualization Tools integrated: chart.js, d3.js, THREEJS, ApexCharts, Globe.gl, KML files generation for Google MAPS → Amazon Web Services: EC2, ECR, CodeCommit, Application Load Balancer, s3 bucket, Secrets Manager My strengths include, → Exceptional expertise in the intricacies of the REACT technology stack. → Strong understanding of HTML, CSS, JavaScript & Typescript. → Efficient in Object Oriented programming languages such as Python. → Clean, reusable, and robust scripting. → Excellent communication skills. → Ability to work as a team. → Able to debug, troubleshoot and problem-solve

𝐎𝐕𝐄𝐑𝐕𝐈𝐄𝐖 𝐀𝐈 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 | 𝐑𝐢𝐬𝐢𝐧𝐠 𝐓𝐚𝐥𝐞𝐧𝐭 | 𝐀𝐈 𝐒𝐲𝐬𝐭𝐞𝐦𝐬 𝐑𝐮𝐧𝐧𝐢𝐧𝐠 𝐢𝐧 𝐏𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 I build AI agents and workflow automations that run in production, not demos: 3,000+ agent runs a month drafting customer emails, researching leads, extracting web data, and updating CRMs, with human review built in. If your team spends hours on repetitive work, here is how I remove it. 𝐀𝐈 𝐄𝐦𝐚𝐢𝐥 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 Your inbox takes too long to manage. I build systems that classify incoming messages, research the sender's history, and draft replies for your approval. My production system drafts replies in under 60 seconds and helped grow API-driven revenue by 15%. 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭𝐬 𝐚𝐧𝐝 𝐖𝐨𝐫𝐤𝐟𝐥𝐨𝐰 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 Your team does manual work a system should handle. I build AI agent systems with custom tools that plug into Slack, WhatsApp, Gmail, and your CRM. The agent does the work, your team approves it, and nothing ships without oversight. 𝐖𝐞𝐛 𝐒𝐜𝐫𝐚𝐩𝐢𝐧𝐠 𝐚𝐧𝐝 𝐁𝐫𝐨𝐰𝐬𝐞𝐫 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 You need data from the web, repeatedly. I build Playwright automations for research, data extraction, and form filling. Hours of manual web work become logged, repeatable pipelines. 𝐂𝐥𝐚𝐮𝐝𝐞 𝐀𝐏𝐈 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 You want AI in your product but need it reliable. I build retrieval (RAG) systems, structured data extraction, and custom agent tools with full observability through Langfuse, so every AI decision can be traced and audited. 𝐀𝐏𝐈 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝐧𝟖𝐧 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 Your tools do not talk to each other. I connect them with n8n pipelines, API integrations, and custom backends. One production build cut manual research time by 60%. 𝐑𝐞𝐬𝐮𝐥𝐭𝐬 𝐅𝐫𝐨𝐦 𝐒𝐲𝐬𝐭𝐞𝐦𝐬 𝐈 𝐇𝐚𝐯𝐞 𝐁𝐮𝐢𝐥𝐭 An AI operations platform for a US trade-data SaaS company: CRM with automated outreach on Claude API and OpenClaw, growing API-driven revenue by 15%. A human-in-the-loop review system with drafting queues, automated tests, and Langfuse tracing across 3,000+ agent runs per month. A tariff classification automation for US import compliance, cutting research time by 60% and classification errors by 30%. 𝐖𝐡𝐲 𝐖𝐨𝐫𝐤 𝐖𝐢𝐭𝐡 𝐌𝐞 Everything I deliver follows production standards: review queues, logging, testing, and observability, so the automation keeps working when inputs get messy. I scope honestly and will tell you upfront if something is not worth automating. Response time is 0 to 4 hours. 𝐒𝐭𝐚𝐜𝐤: Claude API, OpenClaw, Python, Node.js, Playwright, n8n, FastAPI, PostgreSQL, Langfuse, vector search, Docker, REST APIs Describe your most time-consuming workflow in a message and I will tell you exactly how I would automate it.

𝗦𝘁𝗼𝗽 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗖𝗵𝗮𝘁𝗯𝗼𝘁𝘀. 𝗦𝘁𝗮𝗿𝘁 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗔𝘂𝘁𝗼𝗻𝗼𝗺𝗼𝘂𝘀 𝗗𝗶𝗴𝗶𝘁𝗮𝗹 𝗘𝗺𝗽𝗹𝗼𝘆𝗲𝗲𝘀. Most "𝗔𝗜 𝗘𝘅𝗽𝗲𝗿𝘁𝘀" are just prompt engineers. In 2026, a simple chat interface isn't a solution, it's a distraction. I architect Agentic Workflows and Autonomous Systems that execute tasks, analyze complex data, and integrate directly into your business logic, cutting operational overhead by 𝟰𝟬–𝟲𝟬%. I bridge the gap between "𝗖𝗼𝗼𝗹 𝗔𝗜 𝗗𝗲𝗺𝗼𝘀" and "Production-Grade Infrastructure." 𝗛𝗶𝗴𝗵-𝗜𝗺𝗽𝗮𝗰𝘁 𝗔𝗜 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝘀 𝗜 𝗗𝗲𝗹𝗶𝘃𝗲𝗿: - Autonomous AI Agents: Multi-agent systems (LangGraph, CrewAI, AutoGen) with memory, tool usage, and self-correcting multi-step execution. - Production-Grade RAG (Retrieval-Augmented Generation): Hybrid search, re-ranking, and contextual compression for technical/legal datasets to eliminate hallucinations and ensure accuracy. - LLMOps & Cost Engineering: Optimize token usage and latency; orchestrate GPT-4o, Claude 3.5, Llama 3.1, and other LLMs for intelligence & ROI. - Semantic Search & Vector Intelligence: Vector DB expertise (Pinecone, Weaviate, Milvus, Qdrant, FAISS) for deep pattern recognition, recommendations, and enterprise search. - Full-Stack Backend Development: Core Python, Django, FastAPI, Node.js, and serverless architectures for scalable AI-driven applications. - Automation & Orchestration: n8n, Make, Zapier, and custom Python/Node agents for autonomous task execution. 𝗧𝗵𝗲 𝟮𝟬𝟮𝟲 𝗔𝗜 𝗧𝗲𝗰𝗵 𝗦𝘁𝗮𝗰𝗸: - Orchestration: LangChain, LangGraph, LlamaIndex, Semantic Kernel - Models: GPT-4o, Claude 3.5, Google Gemini, Llama 3.1 - Vector DBs: Pinecone, Weaviate, Qdrant, Azure AI Search, FAISS - Backend: Core Python, Django, FastAPI, Node.js, PostgreSQL, MongoDB - Automation: n8n, Make com, GHL, Zapier, Custom Python/Node agents - Deployment: Docker, Kubernetes, AWS Bedrock, Azure OpenAI Service, Hugging Face 𝗪𝗵𝘆 𝗛𝗶𝗿𝗲 𝗮𝗻 𝗔𝗜 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁? AI is only as powerful as the architecture behind it. I ensure SOC2-compliant, secure, and horizontally scalable implementations. I don’t just give prompts, I deliver cognitive systems that provide measurable competitive advantages. 𝗦𝘁𝗼𝗽 𝗴𝘂𝗲𝘀𝘀𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗔𝗜. Click '𝗠𝗲𝘀𝘀𝗮𝗴𝗲' to audit your AI roadmap.

Since 2022, I have been building Python data and automation systems for teams whose work depends on websites, APIs, spreadsheets, databases, and repetitive browser processes. Most projects begin with a simple request: collect this data, connect these tools, or remove this manual step. The real engineering begins when the workflow must run repeatedly, handle changing inputs and failures, prevent duplicates, track progress, and produce usable output. That is the layer I take ownership of. I can help with: • Python data pipelines and ETL workflows • REST API development and third-party integrations • PostgreSQL, MongoDB, MySQL, Airtable, and Google Sheets • Workflow automation with Python and n8n • Large-scale data extraction, browser automation, and OCR • Cin7, GoHighLevel, JustCall, Bol, Shopify, WooCommerce, SendGrid, Slack, and Google Drive integrations Selected systems I have engineered: • Cin7 automation processing 500+ sale orders daily through a hybrid API/browser workflow, with MongoDB, Google Sheets, PDF reporting, reconciliation logs, 99.9% processing accuracy, and a 60% shorter cycle. • A 2M+ complaints pipeline using custom OCR, Selenium, BeautifulSoup, MongoDB progress control, five VPS, and parallel processing. It extracted 20+ fields per record and delivered validated 50,000-row batches within one month. • A 236,000-record Montreal land-evaluation pipeline delivered within 10 days using Playwright, SeleniumBase, MongoDB checkpointing, session management, and 13+ parallel browser instances. It processed up to 54,000 registration numbers per day and extracted 7+ fields per record. • Distributed Python infrastructure across 30+ VPS, processing up to 100,000 Q&A records per day for 18 months. • A JustCall API pipeline organizing 29,000 call-recording records in Airtable, plus Bol, EAN/GTIN, web-to-PostgreSQL, medical-license API, and GoHighLevel-to-Airtable systems. Before development, I clarify the sources, target schema, business rules, frequency, scale, failure conditions, and deployment environment. You receive maintainable code, tested outputs, progress updates, and practical documentation. Send me your current process, source, expected output, and run frequency. I can review it and recommend the most reliable implementation path. 𝗧𝗲𝗰𝗵𝗦𝘁𝗮𝗰𝗸 python, selenium, requests, beautifulsoup, lxml, pandas, multithreading, zyte, tesseract, web scraping, web crawling, automation,scrapers, spiders,real estate properties, e-commerce, lead gen, ai text generation, led database, apartment lists, product catalogs, restaurant, social posts, comments, public dataset, news, ai data, training data, vehicles, serp,google maps, job listing, facebook, instagram followers, twitter, tiktok, reddit, record directory, booking, reviews, hotels, physicians, doctors, search results, people search, google sheets, excel, data mining, shopify, woocommerce, just call, dropbox, pdf extraction, wa systems, serperdev, notion, slack, marketsurge, airtable, microsoft teams, open router, supabase, opencv, langchain, llm integration, data pipeline, docker, cron, linux, mysql, mariadb, sqlite, json, csv, xlsx, txt, webhook, calendly, reportlab, scholars, psychologists lists, deere, physicians extraction, crime data, public qa data, dentists list, car pricing, complains extaction, articles scraping, car dealers leads, movies data, sports data, events data, flights data,crm integration, business operationn automation, finance automation, price monitoring, competitor intelligence, motels data, grapql, erp, databases, vps, self-hosting, ghl, cloud console, flask, hugging face, active campaign, lead connector, onboarding automation, content engine, intelligence engine, statistics scraping, data verification, data enrichment, invoice automation.

Most AI tools fail on specialized documents. CAD drawings, legal briefs, historical archives, medical forms. I build custom intelligent document processing (IDP) pipelines that actually work on your specific document type, at scale. I turn messy, unstructured documents into structured, queryable data. EOBs, legal contracts, construction plan sets, invoices, medical records, architectural drawings. If your team is drowning in PDFs that need extraction, classification, or decision support, that is what I build. I personally architect and deliver every pipeline. My Upwork track record: → Healthcare EOB extraction: OCR pipeline pulling line-item claim data from Explanation of Benefits documents across dozens of payer formats. Structured output validated against schema, ready for downstream billing systems. → Historical corpus processing at scale: Extraction pipeline over 27,000 corporate annual reports (1900-1945) for an academic researcher. Document preprocessing, OCR, structured field extraction, delivered as validated CSV output across production milestones. → Construction and architectural document intelligence: LLM-powered pipelines that read plan sets, spec books, CAD drawing PDFs, and submittal packages. I understand CSI divisions, RFI workflows, and quantity extraction from drawing sets, not just the model layer on top. → Legal contract Q&A (RAG): Retrieval-augmented generation system for querying contract clauses, obligations, and compliance terms across multi-document sets. → Google Document AI integration: 200+ hours billed building production extraction workflows on the Google Document AI platform. → Invoice OCR automation, translation document pipelines, patient document processing: repeat delivery across document types and industries. My stack: Python, Google Document AI, Mistral OCR, PaddleOCR, Tesseract, LangChain, OpenAI API, Gemini, DeepSeek, spaCy, vector databases (Pinecone, Weaviate, pgvector), PostgreSQL. End-to-end: ingestion, preprocessing, OCR, extraction, validation, structured output, API delivery. 100% Job Success. Top Rated. Every project ships to production. Send me a sample document and I will tell you exactly how I would approach it.