Hire the Best DatcoMedia EBis Specialists

I'm an AI Data Annotation & Evaluation Specialist with 3+ years of experience supporting AI, computer vision, and machine learning projects with accurate, high-quality training data. I specialize in image annotation, computer vision, OCR/document annotation, GIS/geospatial labeling, and LLM/AI evaluation. I have experience working with complex annotation guidelines, large datasets, and quality-sensitive projects where accuracy and consistency are critical. What I can help with: • Image & video annotation • Bounding box & object detection • Polygon & instance segmentation • Image classification • OCR & document annotation • Key-value & structured data extraction • Text and formatting annotation • GIS & geospatial annotation • Road sign & geolocation annotation • Chart & visual data annotation • LLM response evaluation • AI judge / model output comparison • Data validation & quality control Tools & Platforms: Roboflow • CVAT • Encord • Labelbox • Label Studio I focus on accuracy, consistency, attention to detail, and following project-specific guidelines. I carefully review annotations, identify inconsistencies, and deliver reliable datasets that are ready for AI model training and evaluation. If you need a dependable AI data specialist who can handle computer vision, document AI, geospatial data, or LLM evaluation, I'd be happy to help with your project.

I'm a detail-oriented professional with a strong background in data annotation, customer service, content moderation, and real estate administration. Over the past six years, I’ve worked with annotation tools such as CVAT, Label Studio, Labelbox, and LiDAR, helping teams build accurate datasets for machine learning projects. I’m also comfortable using Anaconda and PowerShell to support data workflows. In addition to my technical skills, I bring 4 years of customer service experience and 2 years of experience working in real estate administration, where I handled scheduling, document management, and client communications. I also spent 1 year as a content moderator, reviewing and managing digital content for safety and compliance. I take pride in being detail-focused, efficient, and adaptable across different industries. Beyond my work experience, I’ve also invested in my professional growth by completing training in social media management, GoHighLevel CRM, lead generation, and executive virtual assistance. These skills have prepared me to handle tasks from managing online presence and campaigns to supporting executives and clients efficiently. Overall, my blend of hands-on experience, technical skills, and continuous learning makes me a great match for this role, especially if you're looking for someone adaptable, proactive, and results-driven. Tools - Bounding boxes. - Polygon Annotation - Semantic segmentation. - LiDAR annotation. - Landmark/key-point annotation. - Line Annotation (for example, road lines, Streetlights & Road signs). - Cuboid Annotation. - Live annotation (using Anaconda PowerShell tool for sports event) -Calendly Annotation Platform -Remotask 3d&2d Lidar/Lidar lite & segmentation projects -Label Studio -Anaconda Powershell Prompt -CVAT -LabelBox -SuperAnnotation Let us discuss the project and have the best quality for your data set.

Your model is only as smart as the person labeling its data! Bad training data is the #1 reason ML projects miss the accuracy targets. Mislabeled frames and skipped edge cases compound into models that fail on real-world inputs. I am Iqra and I treat your annotation guidelines as a contract. My passion for AI is reflected in my role as a Data Annotation Specialist with hands-on CVAT experience labeling images and video for computer vision models. I deliver pixel-accurate bounding boxes, polygons, and segmentation masks that train production-ready AI not "good enough" data that breaks your model in deployment. ✅ WHAT I ANNOTATE IMAGE ANNOTATION — Bounding boxes, polygons & polylines — Semantic & instance segmentation — Object detection & classification labeling — Landmark & keypoint annotation — Image tagging and categorization TEXT ANNOTATION — Named entity recognition (NER) — Sentiment analysis & intent labeling — Text classification & topic tagging AUDIO & VIDEO ANNOTATION — Transcription and speaker diarization — Audio event tagging & classification — Subtitle alignment and timestampin ✅ Tools I work with daily: CVAT • LabelBox • Label Studio • Roboflow • SuperAnnotate • V7 Labs • Amazon SageMaker Ground Truth • Encord ✅Who I work best with: — ML/AI startups building computer vision or NLP products — Companies running ongoing annotation pipelines who need a reliable long-term labeler — Teams doing RLHF or LLM evaluation work ✅How I work: — I start every project by reviewing your guidelines and annotating a small test batch (20-50 items) so you can verify quality before scaling — I document edge cases as I find them and ask clarifying questions in batches — not one-by-one interruptions → I deliver in your preferred format with a short QA summary noting any uncertain labels for your review — I'm available 30+ hours/week and respond to messages within a few hours during my workday. ✅What you actually get when you hire me: — 98%+ annotation accuracy verified through QA review cycles — Edge cases flagged and discussed — not silently guessed at — Consistent labeling logic across large datasets — Fast turnaround on bulk work without quality drop-off in the last 10% Send me your annotation guidelines and a sample batch — I'll return a labeled test set within 24 hours so you can verify accuracy before committing to a larger contract. Looking forward to helping you build training data your model can actually learn from. Iqra Akram

Your Meta says 40 purchases. GA4 says 28. Your store says 19. Which number do you trust when you decide where to put the next $1,000? I'm a conversion tracking and attribution specialist, and I got here the hard way: I build and run my own ecommerce stores. When the numbers are your own revenue, you can't hand-wave tracking, you have to make it actually work. That's why I know this cold, not from a course, but from fixing it on a live store taking real orders. That gap between platforms isn't a rounding error. It's iOS, ad blockers, cookie consent and browser-only pixels quietly dropping events, so ad platforms optimize on bad data and your ROAS looks worse than it is. I fix it at the source. What I do: - Meta Pixel + Conversions API (CAPI) with shared event_id deduplication. I built this from scratch as a custom mu-plugin on my own live WooCommerce store: browser and server events fire together, deduplicated, so Meta counts each sale once and optimizes on clean data - GA4 setup, audits, and "why don't these numbers match" reconciliation across Meta, GA4 and your store - AI / LLM traffic attribution: ChatGPT, Perplexity and Gemini buyers usually land in GA4 as Direct, and I recover them server-side into a dedicated AI Assistant channel - Google Tag Manager and server-side GTM (Stape) - Google Ads conversion tracking and Enhanced Conversions - Consent mode and GDPR-compliant tracking that still recovers signal - Ecommerce, lead, form and call attribution I also build and run my own Shopify and WooCommerce stores, which is why I read a storefront the same way I read a tag. When I fix your tracking, I understand what it runs on. My proof isn't a slide deck, it's the live store I built and track myself, where the tracking and the storefront both have to work because it's my money on the line. I'm not learning CAPI on your account. I already shipped it on mine.

Hello, I'm Barkilign Mulatu, A Data Scientist and AI/ML Engineer specializing in building production-ready AI systems. From developing Advanced RAG pipelines that "chat with your data" to fine-tuning Multilingual NLP models for niche markets, I bridge the gap between complex research and business value. My approach isn't just about training models; it's about building end-to-end systems that are accurate, interpretable and scalable. Core Areas of Expertise: Generative AI & RAG: Building custom chatbots using LangChain, OpenAI, and Open-Source LLMs. Expert in optimizing retrieval with ChromaDB, FAISS, and Cross-Encoder re-ranking. Natural Language Processing (NLP): Specialized in Named Entity Recognition (NER) and text classification, including multilingual support for languages like Amharic (XLM-Roberta/mBERT). Predictive Analytics & FinTech: Developing credit risk models and scoring systems using XGBoost, Random Forest, and Basel II compliance standards. Full-Stack AI Deployment: Turning models into interactive tools using Streamlit and FastAPI. Technical Toolbox: Languages: Python (Pandas, NumPy, Scikit-learn) AI Frameworks: PyTorch, Hugging Face, LangChain Databases: ChromaDB, FAISS, PostgreSQL Tools: Streamlit, Docker, Git, Telethon (Scraping) My Goal: To provide clear, documented, and high-performing AI solutions that solve your specific challenges—whether that’s automating customer insights or building a custom financial risk engine. Let's hop on a quick message to discuss how we can bring your AI project to life!

I build production AI automation systems and enterprise full stack platforms. I founded RichShorts (richshorts.lol), an AI video automation platform where script generation, avatar rendering, TTS and publishing run as a single automated pipeline. My recent client work includes an AI clip generation service built on Railway and Supabase, using Whisper for transcription and FFmpeg for processing. I also build and maintain Georgia's national geospatial platform, nsdi.gov.ge, under contract with The World Bank, along with maps.gov.ge and internal government systems that operate within the country's public registry ecosystem, which powers 300+ government services nationwide. With 7+ years of enterprise development experience, I specialize in: AI pipelines: LLM integration (OpenAI, Claude), HeyGen, Whisper, FFmpeg, end-to-end pipeline orchestration Full-stack: Node.js, NestJS, Express, PostgreSQL, Oracle PL/SQL Frontend: Angular (v11 to v22, signals and standalone architecture), Vue 3 (Composition API, Pinia), TypeScript, RxJS Geospatial web platforms: OpenLayers, Leaflet, WMS/WFS, INSPIRE-compliant systems Mobile: Ionic/Capacitor app with 100,000+ active users My work is publicly verifiable. Visit nsdi.gov.ge and maps.gov.ge right now and see the platforms I built running in production. I respond quickly, communicate clearly, and deliver maintainable code that your next developer will thank you for.