Hire the Best NLP Engineers
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With a Ph.D. in Interdisciplinary Linguistics, M.A. in English, and 20+ years of experience as a professor, writer, editor, and researcher, I offer professional skills and knowledge in editing, writing, teaching, and consultation regarding linguistics, literature, English grammar, semantics, and computational linguistics. I have taught university courses in all of these subject areas for years, most recently, and mostly, at Tulane University. I am also interested and educated in cognitive science, philosophy of the mind, and self-development. I am a certified tai chi / qi gong instructor and I have written dozens of articles about meditation, neurofeedback, hypnosis, and other related topics. My "interdisciplinary" Ph.D. is interdisciplinary between cognitive, anthropological, and philosophical linguistics. For the last few years I have worked most in computational linguistics, natural language processing, and AI-training by RLHF.

I am a Top-Rated Python Developer with 8+ years of hands-on expertise delivering high-impact solutions across Machine Learning, Automation, NLP, LLM, AI Agent, Web Scraping, and Full-Stack Applications. I specialize in building robust, scalable, production-ready systems that transform raw data into actionable insights and operational success. 🔹 Core Technical Expertise: • Machine Learning & Predictive Analytics: Expert in developing end-to-end predictive maintenance systems, handling feature engineering, EDA, anomaly detection, model building (Decision Trees, Random Forests, XGBoost, Gradient Boosting, k-NN), model evaluation, and deployment using Pickle and Gradio. • NLP & Semantic Search Applications: Built full-stack Streamlit apps with Sentence-Transformer embeddings, integrating semantic search engines with custom cosine similarity scoring and SQLite storage, enabling intelligent content retrieval. • LLM & AI Agent: Built RAG chatbot using LLM with Langchain and Langsmith that specifically designed for customer requirements and handled API orchestration with real time notification service by scheduling and clone job using AI Agent. • Automation & Email Campaign Systems: Engineered secure, personalized email automation pipelines using smtplib, MIME libraries, and pandas, capable of mass email dispatch with live tracking, randomized sending, and user-specific content customization. • Web Scraping & Data Extraction: Developed multi-threaded web crawlers using Requests, BeautifulSoup, Regex, and ThreadPoolExecutor, capable of extracting structured data (e.g., emails) at scale with robust error handling and compliance with ethical scraping practices. • Data Cleansing & Entity Matching: Automated fuzzy matching pipelines leveraging FuzzyWuzzy and Levenshtein Distance to intelligently reconcile messy datasets, achieving high match rates across multi-format Excel datasets. • ETL Pipelines & Data Engineering: Built scalable ETL workflows for ingestion, normalization, and validation of structured and unstructured data from APIs, databases, and file systems using pandas, NumPy, Azure Data Factory, and Alteryx. • Visualization & Reporting: Produced powerful interactive visualizations and dashboards using Matplotlib, Seaborn, Plotly, and Power BI, enabling data-driven decision making for business and technical stakeholders. • Deployment & Optimization: Expert in caching optimization using Streamlit caching, model serialization with Pickle, scalable database storage using SQLite, and efficient deployment pipelines for Python-based web apps and data services. 🌍 Industries Served: Healthcare (Patient Monitoring, Predictive Risk Analysis) Manufacturing (Predictive Maintenance, Anomaly Detection) Retail (Sales Forecasting, Data Cleaning) Technology Startups (NLP Search Systems, Web Automation) Marketing Agencies (Lead Generation, Email Automation) Research & Education (Data Mining, Interactive ML Apps) ✅ What I Deliver: • 🛠️ Clean, production-ready, and scalable Python code • 💡 Business-aligned machine learning and automation solutions • 📈 Insightful, actionable visualizations and reporting dashboards • 🔄 Agile collaboration with flexible time zone availability • 🔒 Data security, compliance (HIPAA, GDPR), and ethical practices • 📩 End-to-end deployment including APIs, dashboards, or deliverables • 🌟 100% client satisfaction and long-term support 🚀 Ready to Transform Your Data or Automate Your Workflow? Whether you need a smart predictive model, a scraping bot, an automation system, or an intelligent search engine, I'm here to build high-quality, customized solutions that drive results. 📩 Let’s connect and turn your ideas into impactful Python solutions!

Full time scraping Guru specializing in web scraping, crawling using python. Worked on projects that deal with automation and website scraping, crawling and exporting data to various data formats (JSON/CSVS). Over the last few years worked with 250+ different individuals/startups/companies and helped them achieve their goals. Here’s what you will get by working with me: * Working only on projects that I can deliver 100% * Ridiculous quality of work * Smart suggestions on increasing results/revenue and decreasing costs * Responsibility for tasks/project I work on * Reliability * Short response time * Excellent written and verbal English skills * Good sense of humor keywords: python, php, java, selenium, requests, beautifulsoup, urllib2, web scraping, web crawling, automation, bots, scrapers, spiders, reverse engineering, linkedin

⭐️ Upwork Rising Talent 🏆 6+ Years of Experience in AI/ML Engineering & Full-Stack Development 💯 Fast Communication with Strong Project Ownership ✅ Practical, Scalable, Production-Ready AI Solutions ⌚ Flexible Availability with Overlapping Business Hours Hey, I'm Asad. I'm a Senior AI/ML Engineer with 6+ years of experience building AI-powered products, intelligent automation systems, and full-stack applications. I specialize in LLM integrations, AI agents, RAG pipelines, NLP, and workflow automation using modern, production-grade AI stacks. I've worked on conversational AI, multi-agent systems, document intelligence, NLP applications, analytics platforms, and AI-assisted SaaS products for startups and growing businesses, building solutions that are fast, practical, and tied to real business outcomes, not over-engineered prototypes. What I Can Do For You: 💠 AI Agent & Multi-Agent System Development LangChain, LangGraph 💠 OpenAI, Anthropic Claude, Gemini & Model Context Protocol (MCP) Integrations 💠 RAG Pipelines, Vector Databases & Knowledge Retrieval 💠 Natural Language Processing (NLP) & Conversational AI 💠 AI Chatbots & Conversational Interfaces 💠 Prompt Engineering & LLM Fine-Tuning 💠 Workflow Automation & AI Orchestration 💠 Python, FastAPI, Node.js & Full-Stack Development 💠 REST APIs, Webhooks & System Integrations 💠 AI-Powered Document Processing & OCR Pipelines 💠 SQL, PostgreSQL, MongoDB & Data Engineering 💠 Cloud Deployment, Scaling & Performance Optimization Let's turn messy data and ideas into production-ready AI systems that actually work.

I am a research engineer focusing upon building and surpassing the latest and greatest in AI. My focus is on natural language processing (NLP) and multimodal (vision and text) AI, with a particular emphasis on large generative models. I have extensive experience working with a variety of different clients, from new startups backed by Y Combinator and AllenAI to large Fortune 500 companies. I have also provided consulting services, including to various venture capital firms and former Microsoft, AWS, and RTL Group executives hoping to build their own AI businesses. I am certified as a top 1% expert on Upwork and within the top 10% by Triplebyte. I also give talks across the industry - for example, I recently spoke on the Weaviate podcast about the current multimodal AI landscape. In terms of the models I am experienced with, I have worked with the vast majority of NLP and multimodal models as well as a significant amount of the speech and vision models available on Huggingface. I regularly build my custom model architectures to best fit client needs since while most models only really have one advancement they focus on, the clients I work with usually would benefit from the improvements from several different Huggingface models. However, I am also familiar with proprietary AI APIs, particularly that of OpenAI’s. I usually recommend those to clients who either will not see a lot of usage of their AI products for a while or those who have low maintenance costs being a top priority. Some of my favorite projects include: - Building a video summarizer taking as input a video or audio file and outputting a summary of its contents in either text or audio format. I used my own custom punctuation addition model, chunking and batching of speech inputs into 10 second increments to speed up transcription, TGlobal attention for the summarization system, and many other tricks. - Building a ChatGPT-style question answering chatbot built entirely with open-source models and tools - Creating a medical bill reimbursement system that took as input a picture of a medical bill, extracted the names of any relevant medical treatments, compared them using semantic search to reimbursable medical procedures in an insurer’s database, and automatically paid out money for all matches - Adding fine-tuning capabilities to MiniGPT-4 and other multimodal LLMs - Domain adapting CLIP on e-commerce data, reaching a 57% relative improvement in zero-shot classification after just 1 hour of training - Creating a custom training framework to train encoder-based language models using the replaced token detection (RTD) objective, including supporting weight sharing, custom generator sizes, training on multilingual datasets, adaptation of models not originally trained with RTD to be trainable using the task, etc. - Building a custom multimodal model architecture using linear attention - Reducing the size of the intent classification and NER models of an automotive company’s Alexa-style virtual assistant by 95-99% while improving accuracy - Creating the state-of-the-art ASL to English translation system back in 2021 (though I surmise this has since been dramatically improved upon since) Tech Stack: Model Development and Optimization - Huggingface, PyTorch, ONNX, Datasets, Pandas, Numpy, Scipy, SciKit-Learn, Sentence Transformers, PEFT, Accelerate, Loralib, TensorRT, Fairseq, LAVIS, TIMM, OpenNMT, TensorFlow, Jax, lots and lots of others Visualization - Matplotlib, tSNE, UMAP LLM Tools - OpenAI API (GPT-4, 3.5 turbo, Ada through davinci, etc.), Langchain, LLaMaIndex, Weaviate, Pinecone, Faiss, ScaNN Cloud - AWS (Sagemaker, EC2), GCP, Azure. I prefer to avoid cloud companies’ end to end AI services (e.g., Amazon Comprehend) since they tend to be inferior to open-source alternatives or things I can custom build, though I am open to using them if that is what you prefer!

AI/ML Engineer — RAG, LLM agents, AI automation, and production MLOps. MS in AI/ML (University of Pittsburgh), US-based, 100% Job Success. 93% retrieval recall, 78% less wasted context, 35% faster hiring. Most AI projects die at the demo. The notebook works, everyone claps, and nobody can ship it. I build LLM and ML systems that survive production. Send me an invite and you'll have a reply within the hour — plus a short Loom walking through how I'd build it, roughly what it costs, and whether it's worth building at all. No obligation, and if the answer is "don't build this," I'll say so. WHAT I'VE SHIPPED — JoinEight: AI hiring engine that cut candidate shortlisting time 35% and lifted offer acceptance — Chex: computer-vision vehicle inspection that sped up checks 60% across multiple locations — Bookafy: smart scheduling with auto-sync that cut no-shows 30% at scale — Cross-document semantic matching with sentence-transformers and FAISS at 93% recall for requirement tracing — Cut irrelevant LLM context injection by 78% with adaptive chunking, and raised generated test-case accuracy to 92% — RAG chatbot for a Swiss banking client and a scalable LLM document-processing pipeline, both 5-star on Upwork 100% Job Success, Top Rated, native English, US business hours. No overnight handoffs, no timezone lag, no waiting until tomorrow for an answer. YOU PROBABLY NEED ME IF — Your RAG pipeline retrieves the wrong chunks and nobody can explain why — A demo works, but there's no path to production, monitoring, or cost control — You need an agent that completes multi-step tasks instead of looping until it burns tokens — Your LLM bill is scaling faster than your usage — You have documents, contracts, or images and need clean structured data out of them — Your n8n, Make or Zapier workflows keep breaking and you want them rebuilt to hold — You've been burned by an AI freelancer who handed over a notebook and disappeared WHAT I BUILD RAG and LLM Search LangChain and LlamaIndex, embedding strategy, chunking, hybrid and re-ranked retrieval, and an evaluation harness so you can prove it got better instead of hoping. Vector stores: Pinecone, FAISS, Qdrant, pgvector. AI Agents and Automation LangGraph, AutoGen and CrewAI when the job needs real engineering. n8n, Make and Zapier when the job is plumbing — with OpenAI and Claude API calls wired in properly instead of duct-taped. Tool selection, multi-step reasoning, guardrails, retries, and hard cost ceilings. Agents that fail loudly instead of silently. Custom ML Models Classification, regression, forecasting, clustering, recommendation, anomaly detection. Scikit-learn, XGBoost, LightGBM, PyTorch, TensorFlow. NLP and Computer Vision Summarization, NER, sentiment, spaCy, NLTK. OCR and document extraction, invoice and form parsing, YOLO, OpenCV. MLOps and Deployment MLflow, Airflow, DVC, Docker, Kubernetes, FastAPI, AWS SageMaker, GCP Vertex AI. CI/CD for models, versioning, monitoring, and a rollback path that exists before you need it. Generative AI Applications GPT-4, Claude, Gemini, LLaMA. Text, image and multimodal, with prompt versioning and evaluation rather than guesswork. INDUSTRIES FinTech and banking, healthcare and MedTech, e-commerce and retail, legal and compliance, real estate and construction, EdTech, and customer support automation. HOW I WORK Weekly demos, not weekly status updates — you see working software, not a percentage. Modular code your team can extend after I'm gone, with documentation and a handover session. Metrics defined before we build, so "done" isn't a matter of opinion. And I'll tell you when a simpler non-AI solution would work better. That conversation has saved clients more money than anything I've built for them. CREDENTIALS MS Computer Science, AI/ML — University of Pittsburgh 100% Job Success, Top Rated on Upwork TELL ME WHAT YOU'RE BUILDING Send me a message with what you're trying to build and where it's stuck. I'll tell you what I'd do first, roughly what it costs, and whether it's worth building at all. If it isn't, I'll say so — that answer is free.