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I help companies turn data and language into intelligent systems using Machine Learning, Deep Learning, and Natural Language Processing (NLP). I hold a Master’s degree in Natural Language Processing and specialize in building and improving models that understand human language. My work focuses on deep learning architectures, language models, and data-driven AI systems for real-world applications. I also bring a research background, having published peer-reviewed papers in NLP and biomedical language models. This experience allows me to approach problems with both scientific rigor and practical engineering skills, ensuring solutions that are robust, scalable, and well-validated. What I can help you with • Natural Language Processing (NLP) solutions • Machine Learning and Deep Learning model development • Large Language Models (LLMs) and transformer-based systems • Text classification, entity recognition, and information extraction • Data analysis and exploratory data analysis (EDA) • Model evaluation, optimization, and experimentation • Data preprocessing and feature engineering • Python-based ML pipelines Research & Publications • Improving Medical Entity Recognition in Spanish by means of Biomedical Language Models — MDPI Electronics (2023) • Generation of Synthetic Sign Language Sentences — IberSPEECH 2021 Education & Specialized Training • Master’s Degree in Natural Language Processing • DeepLearning.AI – Natural Language Processing Specialization • IBM (Coursera) – Exploratory Data Analysis Tools & Technologies Python • PyTorch • TensorFlow • NLP pipelines • Machine Learning • Deep Learning • Data Analysis • Language Models • Text Mining • Neural Networks I’m particularly interested in projects involving NLP, deep learning, language models, and AI research applied to real-world problems. If you’re looking for someone who combinesresearch expertise with practical machine learning development, feel free to reach out. I’d be happy to discuss your project.

🏆 100% JSS | Top Rated ⏱️ Available across US, Canada, Europe, UK, Australia, and preferred time zones 🥇 Experience with teams at Turing, Meta, Google, YouTube (Agentic) 💼 8+ years | 22+ delivered projects | 506+ billed hours Senior AI/ML Engineer LLMs, RAG, Multi-Agent Systems, Python Backends Expert| Deep Learning | Computer Vision I’m Syed Mohsin Ali Shah, Ph.D. (Computer Science), University of Deusto, Spain. I design and deploy production AI that combines Large Language Models, retrieval-augmented generation (RAG), and agentic orchestration with scalable Python services. Focus areas: measurable accuracy, latency reduction, reliability, and maintainability. Core Strengths .) AI & LLM Engineering: GPT-4/5 class, Claude, LLaMA, Mistral; HF Transformers; custom inference servers .) Agentic AI: LangGraph, LangChain, MCP; planner–executor tool use, guardrails, monitoring .) Agentic AI: LangGraph, LangChain, MCP; planner–executor tool use, safeguards, and monitoring .) RAG: Pinecone, Weaviate, Chroma, LlamaIndex; hybrid search, reranking, retrieval evaluation .) NLP: Summarization, NER, structured extraction, document QA, routing Backend & Platforms: .) APIs: FastAPI, Django/DRF, Flask; JWT/OAuth, rate limiting, observability .)Scale & Ops: Docker, CI/CD (GitHub Actions), Redis, Celery, async I/O, streaming .) MLOps: MLflow, experiment tracking, canary releases, automated eval harnesses Machine Learning, Computer Vision & Generative AI: .) Fine-Tuning: LoRA/QLoRA, SFT, preference optimization; prompt/system design .) Vision: YOLO pipelines, OCR (EasyOCR, Tesseract, PaddleOCR), document AI .) Image Gen: SDXL/Flux, DreamBooth, control adapters, safety layers Cloud Based Deployment: .) Cloud: AWS, GCP, Azure, RunPod; GPU hosting, autoscaling, cost control .) Pipelines: ETL/ELT, Spark, batch/stream retrieval layers, vector ETL Quant & Time-Series (Stocks/Crypto): .) Forecasting Models: LSTM/GRU, TCN, Temporal Fusion Transformer, N-BEATS, XGBoost/LightGBM hybrids .) Signal Engineering: multi-horizon forecasts, regime detection, volatility features, market microstructure signals .) Back testing: walk-forward validation, cross-asset/rolling windows, slippage/fees modeling, position sizing .)Deployment: real-time inference APIs, feature stores, event-driven triggers, risk constraints and monitoring .) Use Cases: stock and crypto price prediction, alpha signal research, anomaly detection, and alerting (Research and engineering services only; not financial advice.) What I Deliver: .) Agentic AI platforms (planner/orchestrator + tools: web search, CRMs, booking, calendars) .) RAG chatbots over PDFs, Notion, websites, and email—evaluated for grounding and faithfulness .) High-performance Python backends with FastAPI + Redis for low-latency inference .) LLM cost/latency optimization with caching, prompt shaping, and model routing .) Quant research stacks for equities/crypto: forecasting, signal evaluation, and live endpoints Tooling & Stack: .) Python, FastAPI, Django/DRF, LangGraph, LangChain, MCP, LlamaIndex, HF Transformers, Pinecone, Weaviate, Chroma, MLflow, Redis, Celery, Docker, GitHub Actions, SDXL/Flux, YOLO, OCR toolkits. .) Time-series: PyTorch/Lightning, darts, sktime, prophet (baselines), vector DBs for event retrieval. 💬 Let’s Work Together I build intelligent, reliable, and scalable AI systems from custom GPT apps and multi-agent workflows to high-performance Python APIs with clear communication, fast delivery, and long-term maintainability.

I am Aleksandra, leading a team of experienced full-stack developers specializing in AI-driven applications. We design and develop modern, scalable web and mobile solutions that integrate artificial intelligence, automation, and cloud technologies to optimize business operations. With over 20+ years of collective experience, we have worked with startups and enterprises across industries like FinTech, Healthcare, eCommerce, and SaaS. Our expertise spans the entire development cycle, from initial concept and UI/UX design to backend architecture, AI integration, SRE (Site Reliability Engineering), and cloud deployment. 🏆 194+ successful projects completed on Upwork with global clients 💲 $5M+ earned on Upwork through high-impact full-stack and AI solutions ⏱ 55,121+ hours billed, proving long-term client trust and engagement 💼 600+ total projects delivered since 2000 across AI, web, and mobile 📚 100% of developers hold engineering degrees, ensuring expert-level technical depth 👩‍💻 Advanced AI team includes Kaggle competition masters and top ML researchers 📊 91%+ job success rate, reflecting top-tier performance and consistency 🚀 25+ AI-driven apps deployed in FinTech, EdTech, and HealthTech 🧠 30+ machine learning models built and optimized for live environments 🌎 20+ industries served, from startups to Fortune 500 clients 🧱 Founded in 2000, bringing 24+ years of experience in software innovation 🛠 40+ React + Python full-stack solutions developed for scalable applications ⚡ High-load systems deployed to serve thousands of concurrent users 📈 Client ROI increased by up to 70% in AI automation projects 💬 Featured in Forbes, MBN Magazine, and Helsinki Times for client success stories Expertise: Full-stack development for web and mobile applications AI-powered solutions, including computer vision, natural language processing, and predictive analytics Scalable cloud architecture using AWS, Google Cloud, and Azure Real-time data processing and AI-driven automation Platform Engineering and Infrastructure as Code (IaC) GitOps workflows and CI/CD pipeline optimization API development and third-party service integrations Performance optimisation for high-traffic applications FinOps and cloud cost optimisation Secure and accessible web applications with SEO best practices Technology Stack: Frontend: React.js, Next.js, Vue.js, TypeScript Backend: Node.js, Python (FastAPI, Django, Flask), Golang AI & Machine Learning: TensorFlow, PyTorch, OpenAI API, Hugging Face, LLMOps Databases: PostgreSQL, MongoDB, Redis, Firebase Cloud & DevOps: AWS (Lambda, S3, DynamoDB, EC2), Docker, Kubernetes, Terraform, Helm, ArgoCD, GitHub Actions, GitLab CI/CD, Ansible, Prometheus, Grafana, ELK Stack Tools & Platforms: Figma for UI/UX, Miro for user flow mapping, Webflow for no-code development Why Work With Us? We focus on delivering intelligent, future-proof applications that drive business growth. Our team ensures seamless collaboration, clean code, and scalable architecture that adapts to evolving needs. We are committed to clear communication, efficient execution, and long-term support. If you are looking for a team that can build and scale AI-powered applications with a strong full-stack foundation, let's discuss your project. 🔑 Keywords to find me: AI Developer | Full-Stack Developer | AI Applications | React Developer | Node.js Developer | Python Developer | AI Integration | SaaS Developer | Web App Developer | Mobile App Developer | Scalable Applications | AI-Powered Software | Computer Vision | NLP Engineer | Machine Learning Engineer | Backend Developer | Frontend Developer | Cloud Developer | Automation Engineer | Cloud Architect | GCP | AWS | Azure | TensorFlow | PyTorch | OpenAI | Hugging Face | FastAPI | Django Developer | Flask Developer | Golang Developer | MLOps | LLMOps | DevOps | SRE | Site Reliability Engineer | Platform Engineer | Kubernetes | Docker | Helm | ArgoCD | Terraform | Infrastructure as Code | IaC | GitOps | CI/CD | GitHub Actions | GitLab CI/CD | Jenkins | Ansible | Prometheus | Grafana | Datadog | ELK Stack | DevSecOps | FinOps | AIOps | Observability | Monitoring | Service Mesh | Istio | Crossplane | OpenTelemetry | HashiCorp Vault | Multi-Cloud | Serverless | Figma | Webflow | Miro | Firebase Developer | MongoDB Developer | PostgreSQL | Redis | REST API Developer | API Integration | Predictive Analytics | AI in FinTech | AI in Healthcare | AI in eCommerce | SaaS Application | Intelligent Automation | Real-Time Data Processing | Cross-Platform Developer | SEO-Friendly Development | Secure Web Applications | Scalable Web Architecture | UI/UX Focused Developer | AI SaaS Developer | AI-Powered Mobile Apps | Full-Cycle Development | AI Solutions for Business | Enterprise Software | Startup MVP Development | AI Team Lead | Cloud-Native Applications | Serverless Architecture | AI-Driven Optimization | AI Workflow Automation | Real-Time AI Solutions | AI-Enhanced UX | AI Web App | AI-Powered Dash

Building a custom computer vision application? Need an AI model that actually performs in the real world, rather than just looking good on a testing dataset? Hi, I’m Gebrecherkos. I help startups, researchers, and hardware teams design, train, and deploy high-performance Deep Learning and Computer Vision pipelines. Because my background is heavily rooted in autonomous robotics, I don't just build models—I build robust, lightweight systems that are designed to survive messy, real-time edge deployments. Whether you need to detect anomalies in medical scans, build a custom object detection pipeline, or optimize a neural network for real-time inference, I can bring your AI project to life. 🧠 CORE MACHINE LEARNING & CV CAPABILITIES: 🔹 Computer Vision & Image Processing: End-to-end pipeline development for Object Detection, Semantic Segmentation, and Image Classification. Building and fine-tuning custom CNN architectures (e.g., EfficientNet, ResNet) and U-Net models for binary/multiclass segmentation. Expertise in extensive data augmentation strategies for domain adaptation (blur, jitter, synthetic generation) to ensure models generalize to the real world. 🔹 Advanced Deep Learning Architectures: Designing complex Multimodal Data Fusion systems. Developing and implementing Graph Neural Networks (GNNs) for highly specialized classification tasks (e.g., medical skin lesion classification). Deep expertise in PyTorch and optimizing custom loss functions (Cross-Entropy, Lovász-Softmax) for edge-case accuracy. 🔹 Real-World AI Deployment (The "Robotics" Edge): Unlike pure data scientists, I know how to make AI interact with the physical world. Experience deploying ML models onto edge devices and integrating them with autonomous navigation systems (ROS1/ROS2, SLAM). Proven track record with complex datasets, including underwater Unexploded Ordnance (UXO) detection and highly imbalanced medical imaging. 🛠️ TECH STACK: PyTorch, Scikit-learn, Pandas, OpenCV, Matplotlib, ROS1/ROS2, Linux, Git. Let's build something intelligent. Send me a message with a brief description of your Computer Vision or Machine Learning roadblock, and I will provide a high-level technical approach on how we can solve it—no strings attached.

I'm a Data Scientist and Machine Learning Engineer with a strong specialization in Computer Vision. With hands-on experience building intelligent systems that analyze, interpret, and understand images and videos, I bring deep technical expertise in turning raw visual data into actionable insights. 🔍 Core Expertise: Computer Vision: Object detection, image classification, segmentation, facial recognition, and OCR using PyTorch, TensorFlow, and OpenCV. Machine Learning: Supervised/unsupervised learning, model training, evaluation, and optimization. Deep Learning: Building and fine-tuning CNNs, ResNets, and Transformer-based models for real-world applications. Data Science Workflow: From data preprocessing and feature engineering to visualization and deployment. Deployment: Experience with model deployment via REST APIs, Flask/FastAPI, and cloud platforms like AWS and GCP. I’m passionate about solving complex problems through innovative ML solutions. Whether it's building end-to-end pipelines or optimizing model performance, I focus on delivering clean, scalable, and production-ready code. Let’s build something intelligent together.

I have a degree in Telecommunications Networks Engineering and also possess a minor in Data Science, both gained in university Pompeu Fabra. I have 8 years of experience with Python and about 2 years of experience with LLM. I have experience with RAG and Langchain, development of AI agents and FastAPI. I have extensive experience building end-to-end RAG pipelines. In my recent work at Revolut as an IAM InfoSec, I developed a data pipeline using the Jira API to extract access-request tickets, processing them via LLM-driven analysis (LangChain) for automated reporting. I am comfortable with the entire lifecycle: corpus preparation, embedding generation, and context assembly. I am a strong advocate for "clean code" (typing, testing, and packaging). My experience as a DevOps Intern at Arbolus and a SysOps Engineer at Vendo Services has given me a deep proficiency in Docker, CI/CD (GitHub Actions), and AWS (ECS, RDS, S3), ensuring that the AI applications I build are scalable, observable, and cost-effective. I have experience with auditing the ISO27001 standards which I gained during my stay at AQU Catalunya as well as IT Support at Arbolus. Also, as a SysOps at Vendo, I ensured our company not only to be compliant with ISO27001 standards but also with PCI DSS and GDPR standards. Also, my experience developing Ansible automation and complex configuration scripts aligns perfectly with your requirement for orchestrating services and managing back-office workflows via tools like n8n or Airflow. I did 2 personal projects: In the first one, I have successfully developed autonomous AI agents using LangChain and integrated them into conversational platforms like WhatsApp and Telegram via APIs. Also, I engineered a script for stock market prediction, trained it on Apple stocks and achieved an accuracy rate of 98.5%. I have a C1 level in English and Spanish. I also speak Russian, Catalan, Azeri and a bit of Ukrainian. You can find more information about my previous experience on LinkedIn and also feel free to check my Github (SH-SW). Fun fact, I play chess since I was 4. Being the national champion back in 2014-2015, my highest achievement was getting into top 10 of Europe in youth, with FIDE ELO 1861. Also, my experience developing Ansible automation and complex configuration scripts aligns perfectly with your requirement for orchestrating services and managing back-office workflows via tools like n8n or Airflow. I did 2 personal projects: In the first one, I have successfully developed autonomous AI agents using LangChain and integrated them into conversational platforms like WhatsApp and Telegram via APIs. Also, I engineered a script for stock market prediction, trained it on Apple stocks and achieved an accuracy rate of 98.5%. I have a C1 level in English and Spanish. I also speak Russian, Catalan, Azeri and a bit of Ukrainian. You can find more information about my previous experience on LinkedIn and also feel free to check my Github (SH-SW). Fun fact, I play chess since I was 4. Being the national champion back in 2014-2015, my highest achievement was getting into top 10 of Europe in youth, with FIDE ELO 1861.