Nlp jobs

...work independently and meet project commitments • Willingness to represent professional experience accurately and personally complete all interviews Relevant technologies may include: DevOps/Cloud/SRE: AWS, Azure, GCP, Kubernetes, Docker, Terraform, CI/CD, Linux, monitoring, infrastructure automation and DevSecOps. AI/ML: Python, PyTorch, TensorFlow, scikit-learn, generative AI, LLMs, NLP, computer vision, MLOps, model deployment and cloud ML platforms. Data Engineering: Python, SQL, Spark, Databricks, Snowflake, BigQuery, Redshift, Airflow, Kafka, ETL/ELT, data lakes and data warehouses. How to Apply: Send a direct message containing: • Your résumé • LinkedIn profile • Primary technical area • Years of relevant expe...

I have a corpus of plain text that needs to be explored through topic modeling. The job is strictly data analysis: no data entry or cleaning tasks are required beyond the usual NLP-oriented preprocessing steps. What I expect you to do • Pre-process the text (tokenisation, stop-word removal, lemmatisation, n-grams as needed). • Build and tune one or more unsupervised models—LDA, NMF or any well-justified alternative—for coherent topic extraction. • Interpret each topic with clear keyword lists and, where helpful, short example snippets. • Provide reproducible Python code (Jupyter notebook or .py script) plus a brief write-up of methodology, parameter choices and results. Acceptance criteria • Code runs end-to-end on my machine withou...

I'm seeking a developer to create an AI-integrated Windows application for my law firm. We have a predefined report format, but currently, we manually enter all the necessary details. I want to streamline this process using AI. Requirements: - AI should understand our report format. - Generate reports by inputting details using typed text. - Application sho...report format. - Generate reports by inputting details using typed text. - Application should be user-friendly and secure, given the sensitive nature of legal documents. Ideal Skills and Experience: - Experience in developing AI applications. - Proficiency in Windows app development. - Familiarity with legal documentation and requirements. - Strong understanding of natural language processing (NLP). Looking forward to ...

...paste a YouTube link and instantly receive an AI-generated written summary; • create or upload documents, enhance them as polished PDFs, and perform rich text edits (grammar correction, formatting tweaks, light rewriting); • pay seamlessly for premium usage and manage their own accounts. Core modules I envision 1. YouTube Summarizer – Fetch video transcript automatically. – Run an NLP model (OpenAI, GPT-4, Grok, Claude to condense the content into concise paragraphs. – Display and let users copy or download the summary as PDF or plain text. 2. PDF Creation & Boost – Allow users to upload multiple files, merge them, add comments or highlights, then export a clean, share-ready PDF. – Support conversion f...

...intuitive—fewer clicks from draft to send, clearer confidence scores, and in-context editing without hunting through sub-menus. Visual design tweaks are welcome if they help usability, but the prime target is UX flow. Tech stack The current build sits on a Python backend with FastAPI, PostgreSQL, and a lightweight Vue front end, all containerised in Docker. If you prefer alternative tools for the NLP layer—SpaCy, Hugging Face Transformers, OpenAI API—spell out why and how you’d integrate them. Deliverables 1. Updated codebase with improved response accuracy (validated on my supplied test set). 2. Revised front-end screens focusing on streamlined user experience. 3. Setup/upgrade documentation and a short walkthrough video so my in-house devs can ...

...(2022-2026) so the section feels current and authoritative. Beyond the LR, I’d like to check carefully over the rest of the paper to answer each reviwer comment and be sure each reviewer comment is answered clearly and the writing maintains a consistent scholarly tone. The document is in pdf. When you introduce yourself, include examples of past academic editing—especially if you’ve worked on NLP, computer-vision, or sentiment analysis papers—so I can see your approach. Deliverables • A revised Literature Review rich with analysis, seamless source integration, and recent studies • A change-tracked manuscript showing how every reviewer point has been addressed • A clean, submission-ready version of the paper I’d like the first...

I'm looking for a knowledgeable instructor to teach me how to use Gemini for bot development. Key areas of focus: - Basic setup and configuration - Natural language processing (NLP) features Ideal skills and experience: - Proficiency in Gemini - Strong background in bot development - Expertise in NLP, particularly in sentiment analysis, entity recognition, and text generation - Experience in teaching or tutoring

I need a production-ready conversational agent that focuses purely on information retrieval. The bot must sit seamlessly inside both my website and our upcoming iOS/Android app, answering visitor queries about product details, user-specific account information, and our standard FAQs in real time. Here is what I’m after: • End-to-end development of the chatbot’s NLP pipeline (intent detection, entity extraction, context handling) using a modern framework such as Dialogflow, Rasa, or a custom GPT-based stack—whichever you feel delivers the fastest, most accurate responses. • Secure integration with our product catalogue and user database so the bot can surface personalised account data without exposing sensitive credentials. • Front-end widge...

...have a solid understanding of digital marketing ecosystems, including SEO, content marketing, email workflows, and social media analytics. You possess exceptional written and verbal communication skills with a sharp eye for brand voice and compelling storytelling. You have a strong interest in Artificial Intelligence and marketing automation. Basic familiarity with Natural Language Processing (NLP) concepts or automation tools (like LinkedIn outreach workflows) is a strong plus. The Opportunity: This project is designed as a 3-month launchpad. Because our workflows are heavily rooted in AI and automation, you will gain hands-on experience and walk away with a portfolio of highly sought-after, futuristic marketing skills. For the right freelancer, successful completion of this ...

...need help turning a sizable collection of unstructured finance-related text and document feeds into an accurate, production-ready predictive model. My goal is to spot patterns that reliably forecast the target variables I will share once we start (think risk scores and market-driven KPIs). The raw inputs arrive as news articles, earnings transcripts, and PDF reports, so the first step is a solid NLP-centric pipeline that cleans, tokenises, and extracts meaningful features. I work in a regulated environment, which means the code must be reproducible, well-commented, and easy to audit. Python with libraries such as spaCy, Hugging Face Transformers, pandas, and scikit-learn—or an equivalent stack—makes the most sense to me, but I’m open to a better suggestion as l...

I need an AI voice agent to act as a virtual assistant for inbound calls. The voice agent's primary role will be to provide advisory services based on a knowl...should be able to handle inbound calls. - It must provide advisory services using a provided knowledge base. - The knowledge base will be in PDF format. May handle multiple calls at a time. Need fixed monthly plan / one time preferred Already Have a 8 sim gsm gateway synway 4008. Ideal Skills and Experience: - Experience in developing AI voice agents. - Proficiency in natural language processing (NLP). - Familiarity with integrating voice agents into calling systems. - Ability to work with and interpret information from PDF documents. Please provide examples of similar projects you've completed. Looking forwar...

...machine-learning techniques (NLP, topic modelling, LLMs, classification workflows in Python or R). Together we will review and refine: • the critical sources in each language and define ingestion methods • Build or adapt an AI layer that flags emerging narratives and policy signals for human review • an oversight framework that lets analysts verify, contextualise and, where necessary, override the algorithm’s output • a concise concept paper and proof-of-concept dataset ready for inclusion in an upcoming grant application The formal grant window opens in a few months, so the immediate deliverables are limited to a clear division of labour for the next phase and providing feedback to research design, and lightweight prototype. If you enjo...

...context-aware wording that adjusts to the exact question or concern. The system should log all conversations, flag anything it cannot classify confidently, and let me jump in manually when needed. Please build or integrate with the appropriate APIs—Twilio or similar for SMS, WhatsApp Business API, Facebook Messenger API, and Google Voice—to fetch messages in real time. The AI layer can rely on modern NLP models such as GPT or comparable open-source alternatives, combined with dependable Spanish-to-English translation. All data must remain private; a simple dashboard or email digest showing conversation history and unresolved tickets will be enough for oversight. Deliverables: • A working cloud-hosted or self-hosted application that connects to the four channe...

...are threefold: handle calendar scheduling with smart reminders, fetch facts or real-time information on request, and trigger common home-automation actions such as lights, thermostat, or security scenes. I am looking for an end-to-end build that covers natural-language understanding, speech-to-text, text-to-speech, and a small but polished UI shell for each platform. You are free to choose the NLP stack—Dialogflow, Rasa, or a custom transformer model—so long as latency stays low and the solution can scale. For voice, feel free to tap into native engines (Apple Speech, Google Speech, Web Speech) or a cloud provider like Azure Cognitive Services if it speeds development. Deliverables • Cross-platform codebase with a shared intent engine and separate UI wrappe...

I'm looking for an experienced Node.js developer to set up an AI Router. This intelligent proxy will dynamically distribute Natural Language Processing requests across multiple free AI providers. Requirements: - Support for Natural Language Processing services - Input format: Pl...developer to set up an AI Router. This intelligent proxy will dynamically distribute Natural Language Processing requests across multiple free AI providers. Requirements: - Support for Natural Language Processing services - Input format: Plain text - Dynamic request distribution Ideal Skills and Experience: - Proficiency in Node.js - Experience with AI APIs and proxies - Strong understanding of NLP tasks - Ability to handle plain text input Submit a brief overview of your experience and approach t...

I’m ready to add a smart, conversational layer to my site and need an experienced developer to take the lead. The goal is straightforward: create and deploy an AI-driven chatbot that feels native to the website experience and reliably handles visitor questions in real time. The primary focus here is true AI development....deployment, tested across modern browsers and mobile • A brief admin panel or config file allowing me to update intents, add FAQs, and view basic analytics • Documentation covering setup, customization, and model retraining steps I value clean, well-commented code and transparent communication throughout the build. If you have prior examples of live website chatbots—especially those driven by NLP rather than simple decision trees—p...

...Core: Automated e-commerce API scraping (Amazon, Flipkart) paired with background desktop XML accounting syncing modules. - Utility Framework: Fintech API pipelines for bill payments (BBPS) and webhook transaction logging. - Cross-Platform Frontend: Single Flutter codebase running smoothly at 60 FPS across 15 dynamic categories. - AI Voice Navigation: Native microphone integration connected to cloud NLP engines (Google STT / OpenAI Whisper) for instant page deep-linking. - Embedded Frames: Secure, frame-restricted integration of the TradingView Widget API for study purposes. Added Requirements on Cashback Feature: 1. Cashback Dashboard: Dedicated section highlighting pending/approved cashback details including total earnings from all transactions. 2. Referral Program: Users earn...

...interaction is logged automatically without any manual data entry. I only need straightforward rule-based flows: IVR menus for phone calls, and button- or keyword-driven replies on WhatsApp. Natural-language understanding is not required; speed, reliability, and clear routing rules are the priorities. Please propose the tech stack you’ll use (Twilio, 360dialog, Asterisk, Vonage, Dialogflow CX in “no-NLP” mode, or any other you prefer) along with the integration method for my existing CRM and ticketing tools. A brief outline of how you’ll handle testing and hand-over training will help me evaluate fit. Deliverables should include: • Fully configured call and WhatsApp workflows connected to my CRM and ticketing system • Clean, commente...

...performance, reliability, and cost optimization. * Provide technical leadership through architecture design, hands-on development, code reviews, troubleshooting, and mentoring. ## Required Skills * *8+ years of experience* in AI/ML engineering, architecture, and enterprise solution delivery. * Strong hands-on development experience with *Python*. * Expertise in *Machine Learning, Deep Learning, NLP, and Generative AI/LLMs*. * Strong experience with *RAG, embeddings, vector databases/search, prompt engineering, context engineering, and LLM evaluation*. * Experience with *Agentic AI and model orchestration frameworks*. * Strong hands-on experience with at least one major cloud platform: *Azure, AWS, or GCP*. * Experience with *MLOps/LLMOps, CI/CD, model deployment, monitor...

...must consistently reach at least 90 % accuracy on an independent validation set; precision and recall should be reported alongside overall accuracy so I can see how it performs on both real and fabricated pieces. The workflow I have in mind combines three parts: • an automated pipeline that scrapes or ingests fresh articles, cleans the text, and stores it in a structured format; • a robust NLP model—think transformer-based architecture fine-tuned on a well-curated fake-vs-real news dataset—trained and evaluated in Python with libraries such as PyTorch, TensorFlow or Scikit-learn; • a lightweight interface (REST API or simple web demo) that returns the probability of falseness plus the key features that influenced the decision for transparency. D...

...research fellows on demand. The core idea is simple: a user enters a topic, keyword, DOI or even an abstract snippet and instantly receives the most relevant peer-reviewed papers, neatly ranked with key metadata and brief AI-generated summaries. To make that happen, the tool should draw from open databases such as PubMed, arXiv, Crossref and any other free or licensed sources you recommend, then apply NLP techniques—semantic search, named-entity recognition, topic clustering—to surface only the most pertinent results. A clean web interface or a lightweight desktop app is fine; what matters is accuracy, speed and an intuitive workflow for researchers who will be using it daily. Key deliverables • Source-code repository with clear documentation • Working...

...• n8n will act as the orchestration layer. Your flows should pull in an NLP engine of your choice through n8n’s HTTP or pre-built OpenAI / Dialogflow nodes so intent detection and response generation happen seamlessly. • The agent must cover three core use-cases from day one—customer handling, lead qualification, and product queries—while remaining easy to expand into follow-ups and revenue tracking later. • I’m not yet certain whether our WhatsApp Business API is active. I’ll need you to audit our current setup, advise on any missing Meta Business Manager steps, and connect the final number to n8n once we’re ready. Success looks like 1. A fully documented n8n workflow (export JSON) that includes trigger, NLP proc...

...payment verification and QR/pass-generation capability. 2. Scope of Work The solution must cover the following functional modules, all delivered through a single WhatsApp conversational flow: 2.1 Garba Event Inquiry • Bot should answer common questions: event dates, venue, timings, entry fees, dress code, rules, training schedule, contact details, etc. • Should support natural-language queries (AI/NLP-based understanding), not just rigid keyword menus. • Should offer a quick-reply menu (buttons/lists) alongside free-text understanding, so users can either type naturally or tap options. 2.2 Registration Process • Collect the same data currently captured via our Google Form: name, age/gender, mobile number, address, city, group/family size, etc. (final field lis...

I'm looking for a skilled Python Developer for a small project involving Python development, automation, and AI/LLM integrati...project involving Python development, automation, and AI/LLM integration. Spanish-language experience is especially important. The project will involve working with Spanish content and ensuring that AI-generated results, prompts, and workflows work accurately in Spanish. Requirements Strong Python skills Experience with APIs and automation Experience with OpenAI/LLM APIs Strong Spanish language and NLP experience Ability to work with Spanish prompts and content Clean and maintainable coding skills Good debugging and problem-solving skills Git/GitHub experience is a plus Budget & Engagement Budget: Around $150 Small project Potential for additi...

...Gap Analyzer Developed an AI-powered platform that analyzes resumes against company-specific job requirements. Implemented resume upload and skill extraction using NLP techniques. Built skill-gap analysis to identify missing and required skills. Added company/job-role based analysis and job-readiness scoring. Developed an assessment system with MCQ quizzes and coding tests. Implemented authentication, protected APIs, database integration, and backend services. Built using Node.js, , MongoDB, React.js, and Python/NLP. AutoPulse – Used Car Review Sentiment Analysis () Built an NLP-based system for analyzing customer reviews from used-car platforms. Collected and processed large-scale review data. Performed text preprocessing, cleaning, and sentiment

...must consistently reach at least 90 % accuracy on an independent validation set; precision and recall should be reported alongside overall accuracy so I can see how it performs on both real and fabricated pieces. The workflow I have in mind combines three parts: • an automated pipeline that scrapes or ingests fresh articles, cleans the text, and stores it in a structured format; • a robust NLP model—think transformer-based architecture fine-tuned on a well-curated fake-vs-real news dataset—trained and evaluated in Python with libraries such as PyTorch, TensorFlow or Scikit-learn; • a lightweight interface (REST API or simple web demo) that returns the probability of falseness plus the key features that influenced the decision for transparency. D...

...delivery slot, confirm the booking, and push the details back to our mobile-app backend so everything stays in sync. • Payment handling is out of scope for now; the customer will continue to pay through existing channels. The solution should plug into WhatsApp Business (using the official API or a provider such as Twilio), connect securely to our existing mobile-app database, and rely on a robust NLP engine—Dialogflow, Rasa, or a comparable framework—to understand natural language requests in both English and the local dialect we serve. I will supply sample conversations, price lists, and the current scheduling API endpoints for training and integration. Deliverables I expect: 1. A working WhatsApp chatbot deployed on my verified number and linked to the pr...

...merged cells, multi-page tables, borderless tables, and nested headers. Process multilingual documents, including Indian regional languages. Benchmark and select appropriate OCR engines based on document type and accuracy. 3. Data Extraction & Structuring Convert unstructured web/document content into structured datasets. Design and maintain data schemas. Use rules, regex, layout-aware extraction, NLP/NER, and LLM-assisted extraction where appropriate. Normalize dates, amounts, units, names, addresses, identifiers, and other inconsistent values. Implement deduplication and entity resolution. Maintain taxonomies, classification logic, and reference/master data. 4. Data Quality & Validation Build automated quality checks for completeness, accuracy, freshness, consistenc...

I’m building a cross-platform Flutter mobile app that relies on an “agentic” AI experience driven by natural-language processing. Your task is to own the full Flutter implementation and wire it up to my existing RESTful backend. The AI layer Users will interact with an in-app conversational assistant. You’ll call my NLP endpoint, manage streaming responses, and present them in a chat-style UI while gracefully handling latency, errors, and token limits. The architecture should keep the assistant logic modular so additional skills such as image recognition or predictive analytics can be added later without refactoring the core app. Backend connectivity Two API groups are already documented in OpenAPI (JSON): • Database management endpoints that del...

...drive sell-through, forecast demand at SKU and store level, and surface actionable insights for merchandising and marketing. I expect you to handle everything from data ingestion and cleaning through to model deployment, with clear documentation of assumptions and feature engineering steps. You may use Python (pandas, scikit-learn, XGBoost, Prophet, TensorFlow, or similar), SQL for warehousing, and NLP libraries such as spaCy or transformers for the text components. If you prefer R or another stack, I’m open as long as the final model meets the accuracy and interpretability goals. Deliverables • Cleaned and well-structured datasets ready for modelling • Reproducible notebooks / scripts showing EDA, feature engineering, and model training • A predictiv...

I plan to carry out original AI research with the clear intention of submitting the findings to a peer-reviewed conference or journal. The exact topic is still flexible, yet it will stay within a broad, cross-disciplinary “general AI” scope rather than being limited to NLP, Computer Vision, or Reinforcement Learning alone. I need a collaborator who can help shape the research question, set up experiments, analyse results, and co-author the manuscript to publication standard. Key phases • Literature mapping to identify a novel research gap • Experimental design and implementation (using Python, PyTorch / TensorFlow, or similarly capable stacks) • Rigorous evaluation with reproducible code and well-documented datasets • Full paper write-up&mdas...

I’m building a conversational assistant and need an AI engineer who can take charge of the full Natural Language Processing pipeline for high-quality, context-aware chatbot responses. The core of the project is text generation: designing, training, and fine-tuning a model that answers user prompts fluidly, stays on topic, and preserves an appropriate tone of voice. You’ll work with my existing dialogue data (plus any open-source corpora you recommend) to create a model that can: • Understand multi-turn context and user intent • Respond naturally in English without hallucinating facts • Respect soft constraints I’ll provide on length, formality, and persona Typical tools in this space—Python, PyTorch or TensorFlow, Hugging Face Transformers, a...

...web portal; front-end work is minimal, but clean JSON in/out documentation is essential. You are free to leverage large-language-model APIs (e.g. GPT-4, Claude-3) or an open-source LLM fine-tuned with domain data, as long as you clearly state the stack. Python is preferred for orchestration, but I’m open to alternatives if there’s a compelling speed or cost advantage. Please factor in common NLP libraries—spaCy, LangChain, Hugging Face—and modern vector databases for retrieval-augmented generation if necessary. Turnaround is urgent; I need a functional MVP ASAP. A short demo video or live link that shows “data in, report out” will serve as acceptance criteria, accompanied by a concise setup guide so I can reproduce results locally or in t...

...installable APK or similar package that I can sideload Acceptance criteria 1. Voice/text command executed within two seconds on a mid-range Android phone, offline. 2. At least 10 demo commands covering app launch, navigation, typing, and a simple code snippet insertion. 3. Source code, build instructions, and a brief video showing the assistant in action. If you have experience with on-device NLP (e.g., TensorFlow Lite, , Rasa, or similar) and Android automation APIs like Accessibility Service, I’d love to see your approach and previous work....

I want to build an AI-driven system whose sole focus is content creation. I am still flexible on the exact architecture—whether the core ends up being an NLP model that writes long-form text, a generative image engine, or a multimodal blend, the end goal is the same: reliable, original content produced on demand with minimal human intervention. Here is what I need from you: • A clear proposal outlining the model stack you would use (e.g. GPT-4, Llama 2, Stable Diffusion, or your own fine-tuned variant). • A small proof-of-concept that ingests a prompt and returns publish-ready output. • Documentation describing setup, retraining, and how I can scale the system once the POC is approved. Acceptance criteria: the demo must run locally or on a standard cloud n...

...execution, and dynamic decision-making • Develop agent architectures leveraging planning, tool usage, memory management, and orchestration frameworks • Build systems that enable agents to autonomously resolve customer intents end-to-end Voice & Chat Experience Engineering • Engineer AI-driven voice and chat interaction layers that replace or enhance traditional IVR and scripted bots • Implement NLU/NLP capabilities using LLMs, embeddings, and prompt orchestration • Design flexible, context-aware interactions that dynamically adapt to user input Backend Integration & Action Execution • Build and maintain integrations with enterprise systems through REST/GraphQL APIs, event-driven architectures, and microservices • Enable agents t...

I’m putting together an NLP-driven product and need a hands-on developer who works comfortably in Python and prefers PyTorch as the framework of choice. The immediate goal is to design, train, and fine-tune language models that will power features such as text classification, entity extraction, and semantic search. You should be able to: • architect and code end-to-end pipelines—data ingestion, preprocessing, model training, evaluation, and deployment; • experiment with state-of-the-art transformer architectures, optimise hyperparameters, and benchmark performance on agreed metrics; • containerise and push models to a cloud endpoint (AWS, GCP, or Azure—choose what you know best); • document the approach clearly so the team can reproduce...

I want to build an AI-driven platform that automatically draf...simple interface: the user enters location and concept, presses “Generate”, and receives a ready-to-submit application plus an explanatory report. Python, machine-learning libraries (TensorFlow, PyTorch), NLP techniques for grant language, and a lightweight GIS component will likely be needed, but I am open to your preferred stack as long as accuracy and speed remain high. Payment will follow a subscription model of 300 RON per month for five years, aligning our interests over the long term while keeping the service affordable for small businesses. If you have experience blending data science, NLP, grant writing and web development, let’s talk about an MVP timeline, data sourcing strategy and ...

Claude will be the backbone of a new natural-language-processing system that I’m putting in place for my product. The initial scope centres on three capabilities: reliable text classification, accurate sentiment analysis, and a conversational chatbot that can surface answers from our own content. My training corpus is ready: a large stream of social-media posts plus SEO-focused text collected from our marketing team. I can supply it in JSON or CSV along with basic labels where they already exist. You’ll need to clean, augment, and align this data so it fits neatly into Claude’s fine-tuning workflow (or an equivalent retrieval-augmented approach if that proves more efficient). Here’s what I expect as concrete deliverables: • An end-to-end Claude-compatib...

I need an AI-driven application that automatically searches Google and key government websites for relevant textual information, extracts the material, and turns it into a polished, brand-specific PDF report. The workflow I have in mind is ...sites are Google search results and publicly available government portals, but the architecture should make it simple to add other sources later. • Final output is always a PDF, generated automatically and ready to share. • Code should be clean, well-commented and delivered with a short setup guide so my team can deploy it in our own environment. If you have experience combining web scraping, NLP, and PDF generation—ideally in Python with libraries such as BeautifulSoup, Selenium, spaCy or similar—let’s talk abo...

...and cabs are sourced, priced, quoted, and finally paid for. Here’s the path I need implemented end-to-end: • Meta WhatsApp Cloud API: configure webhooks, templates, and session messaging so automated responses drive the chat. • n8n: build the workflow that catches each message, calls the AI service, branches the logic, and hits the relevant supplier or internal microservice. • AI layer: use NLP to understand intent, gather missing trip details, and hold a natural dialogue until the request is complete. • Travel orchestrator: connect to flight GDS/aggregator, hotel and activity suppliers, plus a cab partner; assemble results, feed them to the pricing engine, and return a clear quotation. • Booking & payment: on customer approval, push t...

...workflow that automatically reviews incoming resumes for my entry-level and mid-level openings, highlights the most relevant candidates, and flags any obvious mismatches. The model should rank applicants primarily on their education background and work experience; other factors can remain optional for now. Here’s what I expect: • A lightweight, reproducible pipeline (Python or similar, leveraging NLP libraries such as spaCy, Hugging Face, or OpenAI embeddings) that ingests PDFs, DOCXs, or text and converts them into structured data. • Scoring logic that weights degree relevance, graduation date, institution, total years in role, and direct title/industry alignment, then returns an ordered shortlist with confidence scores. • A simple dashboard or JSON/C...

...need a solid data-cleaning and preprocessing pipeline: removing noise, normalising case, handling missing or corrupt rows, tokenising, and producing features that make sense for downstream modelling. Once the data quality is reliable, I want a working machine-learning model built on top of it—preferably in Python using well-established libraries such as pandas, scikit-learn, spaCy or a comparable NLP stack. Here is what will let me sign off on the job: • A reproducible script or notebook that takes the original CSV files, cleans them, and outputs a tidy, feature-ready dataset. • A trained text-based model (classification or clustering—I'll decide with you after an initial review of the data) with clear performance metrics and a brief explanation o...

...Hugging Face, and containerisation (Docker/Kubernetes) should feel second nature; if you prefer equivalent tools, I’m open, provided maintainability stays high. Because the insights will feed directly into our live support dashboard, accuracy and low latency are critical. A well-structured test suite, thorough documentation, and CI/CD hooks will be part of the hand-off. Deliverables • End-to-end NLP pipeline (code + Dockerfile) • Trained text-analysis model tuned on my dataset • REST or gRPC service for real-time calls • Documentation covering setup, retraining, and API usage • Unit/integration tests and CI configuration Acceptance criteria • Model must reach agreed precision/recall on a held-out validation set • Average...

...into our ledgers or spreadsheets with zero transcription errors. • Scheduling appointments: sync with Google Workspace and Outlook calendars, recognise time-zone clashes, and send confirmations or reminders automatically. • Monitoring and reporting: watch live account balances, flag anomalies, and produce concise daily summaries in a dashboard or by Slack/Teams message. The build can draw on NLP, RPA, or a conversational AI layer—whichever stack you prefer—provided the final agent plugs smoothly into our finance tools (Excel, QuickBooks, banking APIs, Sage, etc.) and follows industry-standard security practices. Acceptance criteria will be a working demo inside our sandbox environment, full documentation of APIs and prompts, and a short hand-over c...

...Smart escalation rules – if the conversation goes beyond its scope, it must capture the user’s context (browser, device, error codes, recent actions) and hand everything off to our support inbox. • Analytics dashboard so I can track resolution rates, common issues, and gaps in content. Technical freedom is fine—I’m comfortable with solutions built on Dialogflow, Rasa, GPT-based APIs, or a custom NLP stack, provided the end result is reliable, GDPR-compliant, and simple for my team to maintain. Acceptance criteria: 1. Widget embedded on a staging page with my branding. 2. Successful handling of at least 15 predefined technical scenarios in user testing without human intervention. 3. Escalation flow delivers complete transcripts and metadata to our ...

...or configuration with inline comments and rollback instructions • Before-and-after metrics demonstrating accuracy regained and measurable response-time gains Acceptance criteria: zero incorrect replies in a 200-turn regression test and an average response time no slower than 800 ms under the current traffic profile. Tools and languages are flexible as long as you work comfortably with modern NLP/LLM frameworks, Python or Node back-ends, and cloud deployment pipelines (e.g., Docker, AWS/GCP, Git). Push changes through a feature branch so I can review via pull request before merging to production....

I need an AI-powered web application that focuses exclusively on corporate law. The system must be able to: • Offer conversational, context-aware legal advice on corporate matters. • Draft standard corporate documents (NDAs, shareholder agreements, board resolutions, etc.) from user-supplied ...and a short video walkthrough. Acceptance criteria • Advice responses cite at least three authoritative sources. • Generated documents are ready to download as Word or PDF. • Research mode returns links to statutes and cases, organised by jurisdiction. • System deployed to my cloud account and passes a brief user test covering the three core functions. Please include examples of previous NLP or legal-tech work and indicate which stack you would choose ...

Role AI / Machine Learning Engineer – Large Language Models & Clinical NLP We are looking for an experienced AI/ML researcher or engineer to support a research project focused on automated clinical data abstraction from pediatric congenital heart surgery records using locally deployed open-weight large language models. Project Automated Clinical Abstraction in Pediatric Congenital Heart Surgery Using Open-Weight Large Language Models: Extraction of Diagnoses, Procedures, and Surgical Risk Categories The project aims to evaluate whether open-weight LLMs running locally can accurately extract structured clinical information from unstructured medical documents, including: * Operative notes * Discharge summaries * Echocardiography reports * Cardiac catheterisation report...

...introductory theory. You should be comfortable switching between conceptual explanations and hands-on coding demonstrations (Python, Jupyter, TensorFlow/PyTorch, scikit-learn). Clear, native-quality Japanese communication is essential; all slides, code comments, and Q&A will be in Japanese. To keep the engagement high I expect: • A concise syllabus that shows how you will sequence ML, DL, and NLP topics over the proposed calendar • Total duration of the course will be 40 hours • Practical assignments after each session and prompt feedback on submissions • Session recordings made available to participants for later review Success is defined by participants working experience with the given tools for min 6 years and have fluency in japanese speak...