Hire the Best PrimeFaces Specialists
in Turkey

Hi, I’m Hilal 👋 I’m an AI/ML Engineer focused on building and deploying production-ready ML and LLM systems. I work across the full lifecycle — from data pipelines and model development to APIs, containerization, CI/CD, cloud infrastructure, monitoring, and LLM observability. I’m especially interested in systems that need to work reliably outside a notebook. My recent work includes multi-agent systems with LangGraph, advanced RAG pipelines, LLM gateways and fallback routing, evaluation pipelines, and cloud-native deployments on Kubernetes. 🛠️ What I can help with: 🧠 LLM & Agentic Systems: LangGraph, LangChain, LiteLLM, multi-agent workflows, prompt/version management 🔎 RAG: Hybrid retrieval, reranking, Qdrant, ChromaDB, FAISS, embeddings, retrieval evaluation 📊 LLMOps & Evaluation: Langfuse, Ragas, DeepEval, tracing, model/provider monitoring ⚙️ MLOps: MLflow, Docker, Jenkins CI/CD, model deployment, reproducible pipelines ☁️ Cloud & Infrastructure: Kubernetes, GKE, Terraform/IaC, distributed systems, S3/MinIO, PostgreSQL, Nginx 📈 Observability: Prometheus, Grafana, Alertmanager, structured monitoring and performance analysis 💻 Backend & Data: Python, FastAPI, REST APIs, SQL, Polars, Pandas, NumPy, ETL, feature engineering 🏔️ One of my recent projects, CairnOps, is a production-style multi-agent AI system built with LangGraph, RAG, LiteLLM, Langfuse, and cloud-native infrastructure. It helped me work through real engineering problems such as model fallback, trace correlation, evaluation, memory constraints, and deployment architecture. 🛰️ In OrbitDecay, I worked on performance-heavy data processing and MLOps architecture, including moving CPU-bound workloads out of Python with a custom Rust/Polars integration. 🏥 I previously worked as a physiotherapist, which gives me practical domain experience for healthcare and biomedical AI projects. My current focus is AI engineering and production ML/LLM systems. 📩 If you need help taking an ML or LLM project from prototype to a maintainable production system, feel free to message me.

End-to-End AI/ML Engineer | Predictive Systems | NLP & GenAI Solutions Turn Data into Decisions — Real-World Machine Learning That Scales I help companies turn data into actionable, revenue-generating systems using machine learning, generative AI, and advanced analytics. With years of experience in delivering production-ready AI pipelines, I’ve enabled organisations to automate processes, improve forecasting accuracy, and deploy intelligent agents at scale. ✅ Proven ML Impact 🧠 Delivered 60+ AI/ML projects, including LLM apps, forecasting tools, and automation pipelines 📈 Helped clients improve prediction accuracy by up to 45% and save 1000+ labour hours annually 🚀 Built fully functional ML solutions from prototype to cloud deployment (AWS, GCP, Docker) 🔍 Designed interpretable ML models using SHAP, LIME, and robust validation methods 🧠 Core Machine Learning & AI Expertise Machine Learning: Supervised/Unsupervised Learning (scikit-learn, XGBoost, LightGBM, CatBoost) Time-Series Forecasting (Prophet, ARIMA, LSTM) Model evaluation, hyperparameter tuning, pipeline automation SHAP / Explainable ML / Feature engineering best practices LLM & Generative AI: OpenAI GPT-4, Claude, Mistral integration RAG pipelines with LangChain / LlamaIndex Custom agents using AutoGen / CrewAI Prompt optimisation for task-specific NLP apps NLP Systems: Text classification, summarisation, and named entity recognition (NER) Semantic search using Sentence Transformers / SBERT Fine-tuning transformers for domain-specific tasks MLOps & Deployment: API deployment using FastAPI / Flask Dockerized services and CI/CD pipelines Tracking with MLflow / Weights & Biases AWS (SageMaker, Lambda), GCP, Azure Data Engineering: ETL pipelines (Pandas, Dask, SQL, Airflow) Web scraping (Scrapy, Selenium) Data preprocessing & imputation workflows 🧩 Industry Solutions I’ve Built 🏥 Healthcare & Wellness Built LSTM-based appointment forecasting models Engineered patient triage bots using LLM + medical knowledge bases 📈 Finance & Risk Fraud detection systems with XGBoost & SHAP explanations AI-powered credit risk scoring pipelines 🏢 Real Estate Property price estimators using multi-source data (Zillow + internal CRM) Automated investment analysis dashboards 📊 Retail & E-commerce Recommender systems and demand forecasting AI-based pricing and inventory optimisation 📄 Legal & Compliance NLP tools for contract review and legal clause extraction Built compliance chatbots with SEC/FINRA document alignment 🔧 Why Clients Trust Me for AI/ML Engineering ✅ Full-Stack AI Engineer: Model → API → Dashboard 🔒 Secure & Scalable: Follows best practices in ML lifecycle & data privacy 📊 ROI-Driven: Weekly progress tracking with measurable KPIs 🚀 Delivery-Focused: MVP in 2–3 weeks, production in 30–45 days 🤝 Let’s Build Your Next AI System I work with startups and enterprises to build scalable ML solutions that power decisions, automate workflows, and increase profitability. 📩 Free AI/ML Blueprint: Tell me your challenge, I’ll send back a custom roadmap in 48 hours (no cost, no pressure).

Hi, I am an AI & Machine Learning Engineer specializing in Perception 3D, Computer Vision, Edge Computing, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Chatbot Development, Generative AI, Embedded Systems, and Firmware Development. Please get in touch if you need help with the following: • Machine Learning & Deep Learning model development • Computer Vision tasks like object detection, segmentation, and 3D reconstruction • Natural Language Processing (NLP) including text mining, sentiment analysis, and chatbots • Generative AI models for stock prediction, image inpainting, and virtual clothing • Time-Series Forecasting and Anomaly Detection • Firmware development for microcontrollers (ESP32, STM32, PIC) and IoT devices • Schematic and PCB design using Altium, KiCad, Eagle, and EasyEda • AWS IoT Core setup and cloud integration for IoT projects • Device driver development for various peripherals (I2C, SPI, etc.) • AI Deployment & MLOps with AWS, GCP, Docker, and Kubernetes • Data Analysis & Visualization for business intelligence Tools and technologies I use: • Python, C++, R, JavaScript • TensorFlow, Keras, PyTorch, Scikit-Learn, HuggingFace, LangChain • Zephyr RTOS, FreeRTOS, ESP-IDF • Flask, Django, Node.js • AWS IoT Core, GCP, Docker, Kubernetes • Altium, KiCad, Eagle, EasyEda • MongoDB, MySQL, PostgreSQL, Cloud SQL • Pandas, NumPy, Matplotlib, Seaborn, SciPy Do reach out if you need something other than this, I may be able to help out and guide.

I help startups and engineering teams ship faster by integrating AI-first development workflows, LLM agents, custom MCP servers, local/cloud AI models, and production-ready automation into real codebases. I use tools like Claude Code, Codex, OpenCode, LM Studio, llama.cpp, and other AI engineering tools in production every day. I design structured .md workflow files, repo instructions, agent rules, and context-management systems that reduce token waste and make AI-assisted development predictable, efficient, and scalable. What I can help with: - LLM agents for existing or new products - Custom MCP servers and AI tooling around your workflow - AI-assisted development process implementation - Claude Code / Codex / local LLM setup for teams - RAG, automation, codebase analysis, internal dev agents - Fullstack development across web, mobile, desktop, embedded, and gamedev - Local and cloud model integration - Rapid prototyping and production-grade implementation I am not tied to one stack. I have 20+ years of commercial software engineering experience in startups, and 10+ years in open source as the author of multiple libraries and frameworks. Core technologies: C, Objective-C, Swift, JavaScript, TypeScript, Java, Kotlin, Python, embedded systems, game development, web, mobile, and backend systems. I work remotely only. My focus is simple: help your team build faster, reduce engineering friction, and turn AI tools into a real production advantage.

I craft production-grade AI image pipelines for photoreal portraits, creative styles, and explainable imaging. My work combines Stable Diffusion SDXL, LoRA, ControlNet, IP-Adapter, and FaceSwap/InSwapper to deliver consistent identity, natural skin, and professional-quality outputs. Recent highlights include: Deploying AI generators on Replicate with dynamic LoRA loading, QA scoring, and Docker CI/CD. Delivering studio-quality headshots with ArcFace ID consistency and 4K tiled refinement. Creating anime/creative styles with LoRA + identity-preserving FaceSwap pipelines, optimized for e-commerce, HR, and content creators. Beyond AI, I bring an academic foundation as an Applied Mathematics MSc with a published paper (“Web Application for Step Size Strategies”) and an ICMME2021 conference presentation (COVID-19 analysis with LaTeX Beamer). This background allows me to also support clients with LaTeX-based technical documentation—ensuring accuracy in formulas, references, and structure. Tech stack: Stable Diffusion SDXL, LoRA, ControlNet, IP-Adapter, ArcFace, InsightFace, FaceSwap/InSwapper, Gradio, Replicate/Cog, Docker, Python, LaTeX/Overleaf, Git/GitHub. 🚀 Whether you need high-end AI image pipelines or polished LaTeX documentation, I deliver fast, reproducible, and research-level quality.