Urgent NLP & Automation Engineer for PoC

@ZohaibRoy

⭐⭐⭐⭐⭐ Deliver Efficient NLP Solutions for Vendor/Product Mapping ❇️ Hi My Friend, I hope you're doing well. I’ve reviewed your project details and see you are looking for an experienced NLP and automation engineer. You don’t need to look any further; Zohaib is here to help! My team has successfully completed 50+ similar projects for NLP solutions. I will quickly create a working PoC that maps vendor/product strings to NIST CPE identifiers within the next 9 hours. ➡️ Why Me? I have 5 years of experience in NLP and automation, specializing in string normalization, embedding generation, and fuzzy matching. My expertise includes Python programming, ONNX integration, and data processing. Additionally, I have a strong grip on related technologies, ensuring that I can deliver a robust solution efficiently. ➡️ Let's have a quick chat to discuss your project in detail. I can share samples of my previous work and demonstrate how I can meet your needs effectively. Looking forward to our conversation! ➡️ Skills & Experience: ✅ Python Programming ✅ NLP Techniques ✅ ONNX Export ✅ DistilBERT Embeddings ✅ Fuzzy String Matching ✅ Data Normalization ✅ PowerShell Scripting ✅ Cosine Similarity ✅ Token Cleanup ✅ Alias Resolution ✅ Scoring Formulas ✅ Project Management Waiting for your response! Best Regards, Zohaib

@sajjadtaghvaeifr

Hello, I trust you're doing well. I am well experienced in machine learning algorithms, with nearly a decade of hands-on practice. My expertise lies in developing various artificial intelligence algorithms, including the one you require, using Matlab, Python, and similar tools. I hold a doctorate from Tohoku University and have a number of publications in the same subject. My portfolio, which showcases my past work, is available for your review. Your project piqued my interest, and I would be delighted to be part of it. Let's connect to discuss in detail. Warm regards. please check my portfolio link: https://www.freelancer.com/u/sajjadtaghvaeifr

@nikhilgarg96

Hello, With a broad background in the full software development life cycle, I am confident that my expertise in Python and my experience across different domains make me the right fit for your project. I am skilled in leveraging the power of NLP, which will be essential for preprocessing and normalizing the vendor/product strings you need. I also have hands-on experience with transformer models, particularly BERT and similar embeddings systems, which will be crucial for this task. Moreover, my proficiency in ONNX export and inference enables me to build and demonstrate a PoC with reproducible code while efficiently computing the similarity between inputs according to your requirements using cosine similarity. Additionally, my familiarity with fuzzy string matching will prove valuable for encoding classical fuzzy scores needed for your solution. Regarding your timeline, I appreciate the urgency of this project and can assure you a fast turnaround without sacrificing quality. In fact, I can commit to providing all the deliverables you require within the 9-hour timeframe you've indicated. In sum, consider me as a developer who not only understands how systems work but has successfully delivered complex projects within tight deadlines. Let's collaborate on this time-sensitive mission and bring efficiency through intelligent automation using NLP. Thank you

@koolvishruth

With years of hands-on experience in software development, including expertise in Machine Learning and Automation, I bring a skill set that aligns perfectly with your project requirements. To address a similar task in the past, I developed a fully automated system that employed Python, ML, and AI techniques to preprocess and normalize raw data, apply alias resolution and rule-based normalization, compute similarity using BERT-style embeddings with classical fuzzy scores through a ranking layer and finally applying simple heuristics for version handling and multi-candidate resolution. I can adapt and replicate the proven strategy for your task efficiently. I'm no stranger to time-sensitive tasks and delivering under strict deadlines as this request demands. Given the specifics of your task - from ingesting data to generating embeddings for both inputs and NIST CPE titles using a lightweight transformer (DistilBERT) exported to ONNX, computing similarity (cosine) between inputs and CPE candidates, to combining embedding similarity with classical fuzzy scores (Levenshtein / Jaro-Winkler) via a ranking layer - I can confidently say that I will complete this PoC within the 9-hour timeframe given my deep understanding of these technologies.

@abhisaini0188

Hello, Thank you so much for posting this opportunity. It sounds like a great fit, and I’d love to be part of it! I’ve worked on similar projects before, and I’m confident I can bring real value to your project. I’m passionate about what I do and always aim to deliver work that’s not only high-quality but also makes things easier and smoother for my clients. Feel free to take a quick look at my profile to see some of the work I’ve done in the past. If it feels like a good match, I’d be happy to chat further about your project and how I can help bring it to life. I’m available to get started right away and will give this project my full attention from day one. Let’s connect and see how we can make this a success together! Looking forward to hearing from you soon. With Regards! Abhishek Saini

@gm341473

In the realm of AI and Automation, I've refined my proficiencies in NLP, Machine Learning (ML), Deep Learning, and Python, which I believe sets me up tremendously well for your PoC project. More specifically, over the course of my career, I have honed deep expertise in BERT-style embeddings - something I notice was listed as a mandatory qualification. Furthermore, I've had ample practice working with ONNX export and inference development as well as familiarity with fuzzy string matching, which your project calls for. Drawing from my experience, I have encountered numerous projects that demanded stringent deadlines and fast-paced deliveries similar to yours. As a result,I've cultivated a knack for producing results promptly without compromising the quality code. To give you a tangible example from my past work; recently, I had a task to develop an ML model to analyze customer sentiments for a complaint resolution system in just under 12 hours- and managed to deliver not just within time but also impressed the client by its precision. To assure you of flawless Casse-Represntation Project (like raw vendor/product names to canonical NIST CPE identifiers mapping) completion within 9 hours, I will make the assumption that you'll provide dataframe format data set that can be easily transformed into numpy nd array by pandas. This would help speed up formatting asnd stemming tasks.

@GameOfWords

Urgent NLP & Automation Engineer for PoC ⚠ NO PAYMENT UNLESS YOU'RE SATISFIED ⚠ As an experienced mobile app developer with a strong focus on Android applications, I am uniquely qualified to build a sophisticated browser app that aligns perfectly with the multi-faceted specifications you've listed. Throughout my 5+ years in this field, I have mastered the art of creating harmonious user interfaces and delivering quick, personalized results. This, combined with my deep knowledge of React Native and Flutter, will ensure your app is not only lightweight and fast, but also resolute in privacy protection. One of the key features you require is a Proxy System. Having worked on similar projects before, I have a thorough understanding of implementing automatic proxy activation while prioritizing user privacy. Furthermore, having expertise in AI-powered technologies including computer vision models gives me a unique advantage for seamlessly integrating an efficient Ad block system while carefully preserving the monetization capability you seek. I guarantee transparent communication and milestone-based delivery to ensure your full satisfaction with every aspect of the project. Together, we can bring your vision for a fully-featured browser app with a time frame of 15 days and within your budget to life. Let's start creating something impactful together!

@DGM999

Hello, I’ve carefully reviewed your project and know exactly how to deliver results that are strategic, efficient, and tailored to your goals with no wasted time or guesswork, just real, measurable value. With several years of hands-on experience in Python, Machine Learning (ML), Powershell, Data Cleansing, Deep Learning, Natural Language Processing, BERT, I bring not just expertise but a track record of delivering results that help clients move forward with confidence. My Portfolio: https://www.freelancer.ca/u/DGM999 If you’re looking for reliable, quality-driven support, I’m just a message away. Let’s make it happen. Best Regards, Sadat Saeed

@issamelimrany1

I’ll build your full 9-hour PoC—string normalization, aliasing, ONNX embeddings, fuzzy scoring, ranked CPE matching, PowerShell demo, and evaluation CSV—fast and clean.

@Baehaki0315

Hi Jovan, I fully understand the importance of delivering a timely Proof of Concept (PoC) for mapping vendor/product strings to NIST CPE identifiers. I'm ready to tackle this urgent challenge with speed and precision. ✅ My Plan: - Ingest the raw vendor/product names and preprocess them (lowercasing, locale suffix removal, token cleanup). - Apply alias resolution and rule-based normalization effectively. - Utilize DistilBERT for embeddings and export it to ONNX for lightweight inference. - Compute cosine similarity and combine it with fuzzy scores using Levenshtein or Jaro-Winkler. - Output the top N CPE matches with confidence scores and heuristics for version handling. In a previous project, I successfully developed a real-time product matching system where I faced challenges with noisy data. By implementing effective preprocessing and embedding strategies, I achieved a matching accuracy exceeding 90%. With 5 years of experience in NLP and automation, I specialize in BERT-based solutions, ONNX, and PowerShell. I’m committed to delivering your PoC within the 9-hour timeline. Thanks,

@sadam61

Dear Jovan, I am confident in delivering the urgent PoC within the 9-hour window you require. With over 9 years of advanced Python development experience, including deep expertise in NLP, BERT-style embeddings, ONNX export/inference, and fuzzy string matching, I am well-equipped to handle this complex integration efficiently. I have successfully implemented similar solutions, for example, automating entity resolution across noisy product datasets by combining transformer embeddings with heuristic fuzzy matching to achieve high precision and robust performance. The core challenge was balancing embedding similarity and lexical fuzziness, which I resolved through a custom ranking layer that dynamically weighted these signals, ensuring accurate candidate selection. Assumptions include availability of sample data and metadata for the NVD/CPE set and that ONNX runtime is supported in your environment. I will start immediately upon confirmation and commit to delivering a clean, well-documented, fully reproducible PoC within the deadline. Looking forward to your response. Best regards, Sadam

@ivank69

Hi, client. Should I use your provided CPE list or fetch the latest from NVD? Are version numbers part of the match or handled separately? I’ve built similar tools combining DistilBERT + fuzzy matching to normalize noisy vendor names to CPEs. In one project, I mapped scan outputs to NIST CPEs using ONNX-exported embeddings and hybrid scoring. The main challenge was resolving aliases and scoring edge cases, which I solved with a weighted combo of cosine + Jaro-Winkler + heuristics. Plan (deliverable in 8–9 hrs): Preprocess raw strings + alias map Embed raw/CPE names (DistilBERT → ONNX → onnxruntime) Score with cosine + fuzzy logic Rank top CPEs with confidence Output: Python script, ONNX model + PowerShell runner, sample CSV, and README Ready to start now and deliver on time. Best,

@ikramelahihashmi

Hi, I have reviewed the job description and I'm ready to start immediately. I guarantee 100% quality based on similar tasks I have completed, and I can offer you a 10% discount for this project. Please contact me so we can discuss the job and begin working on it.

@Abutalha5

Hi, I am Abutalha, experienced in NLP, ONNX workflows, and fuzzy-matching pipelines, with past work mapping noisy software strings to structured security taxonomies. In a similar project for an enterprise vulnerability platform, I built a transformer-based resolver combining BERT embeddings, alias rules, and fuzzy scores to match unstandardized vendor/product names to a controlled product registry. The main challenge was noisy text with many near-duplicates, which I solved by layering rule-based cleanup with embedding similarity and a weighted ranking function. For your PoC, I will rapidly preprocess raw strings, apply alias/normalization rules, generate ONNX-based embeddings, compute cosine + fuzzy scores, rank top CPE candidates, and deliver a runnable Python prototype, PowerShell ONNX inference snippet, README, and evaluation CSV. I estimate 8–9 hours to complete the full PoC and can start immediately. Best regards, Abutalha.

@SolutionMart

My name is "Usama Safdar" and I am a Ph.D degree holder which means I am highly-capable to tackle this project "Content Editor " with 100 percent accuracy. I am a professional writer with over 6 years of experience in writing; Essays, Research Summaries, Thesis, Dissertation, Lab Reports and Case Studies. I always provide High-Quality Solutions within the shortest possible time with all instructions followed against very reasonable prices. I can manage works even with shortest deadlines like; "2500 words work in just 6 Hours" with very reasonable time. As a pro academic writer I am also familiar with all the referencing styles; such as APA, Harvard, OSCOLA, IEE, MLA etc. I always provide plagiarism-free solutions and as a prove I also provide "FREE Turnitin reports". For Samples, please visit my profile https://www.freelancer.com/u/SolutionMart Please message me to start the discussion. Thank You

@TopWritingGuru

My name is Rabia Faisal, I am working in the writing industry since 2011. During this time, I have served countless clients with a full amount of satisfaction by providing them with TOP Quality Solutions. I have command of all references APA, Harvard, IEEE, MLA & Chicago, etc. I will provide plagiarism-free work with 100 percent accurate grammar within your given deadline. Please message me to get Top Class Services. I am waiting; https://www.freelancer.com/u/TopWritingGuru

@oleksandrf3

I'm ready to complete in the highest quality. Hi there, Your project aligns perfectly with my expertise in NLP-based normalization, ONNX transformer deployment, and fast prototyping. I have recently delivered a PoC for a Fortune 500 client mapping noisy manufacturer/device data to standardized GS1, utilizing BERT-like embeddings, classic fuzzy matchers, and reproducible ONNX models. The main challenge was balancing accuracy with low inference latency, which I solved by combining token-preprocessed embeddings with lightweight post-ranking and fast ONNX inference, triggered via CLI and Python script. For your 9-hour PoC, I can immediately start by: 1) Engineering robust preprocessing and alias normalization, 2) Setting up CPE and input embedding generation with DistilBERT ONNX, 3) Integrating PowerShell-based ONNX scoring, 4) Ranking via hybrid similarity, and 5) Producing reproducible evaluations as requested. Assuming raw strings are English and enough NVD sample data is provided, I estimate full delivery on time, with clear documentation and tailored heuristics to maximize match precision. Let’s connect now so I can deliver results within your deadline. Thank you for your time, Oleksandr

@dushyant317

with 13+ years of experience delivering high-impact,. Expert in requirements analysis, solution formulation, and compliance alignment. Proven track record across diverse industries and high-value . Skilled in crafting clear, persuasive, and technically robust . Focused on maximizing win rates through strategy, precision, and quality.

@markupdudes

Hi, I understand the urgency and technical complexity of your PoC requirement to map noisy vendor/product strings to canonical NIST CPE identifiers within 9 hours. With extensive experience in NLP, BERT embeddings, ONNX deployment, and string similarity techniques, I am confident in delivering a reproducible Python prototype swiftly. I recently completed a similar project involving fuzzy matching and embedding-based normalization for product categorization, where the main challenge was balancing embedding similarity with classical fuzzy metrics for accuracy. I solved this by combining cosine similarity with Jaro-Winkler scores in a weighted ranking system, ensuring robust multi-candidate resolution. My plan includes rapid preprocessing and normalization, ONNX embedding inference using DistilBERT, integration with classical fuzzy matching, and delivering the prototype plus PowerShell integration snippet as requested. I can start immediately and propose to complete this within the 9-hour deadline. Could you please confirm the size and format of the raw vendor/product list to ensure optimal preprocessing within the tight timeline? Best regards,