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**📝 Profile Context / Summary** With 10+ years across enterprise IT and global freelancing, I am an AI-Stack Architect—not just a full-stack developer. In 2026, the industry has shifted decisively: software is no longer just written; it is architected, governed, and continuously learned. The most valuable engineers are no longer those who simply write code, but those who can turn code into cognition—engineers fluent in the AI-stack. I am that engineer. I design and build agentic platforms—systems where AI doesn't just assist but actively plans, builds, tests, and releases software. I have successfully delivered complex solutions across Medical, Fintech, Employee Management, and SaaS industries, handling everything from AI-native frontends to hyper-scalable microservices with autonomous agent orchestration. **🤖 AGENTIC AI & MACHINE LEARNING** 2026 is the breakout year of AI inferencing—where trained models generate predictions and outputs from new data. Most AI computing is now spent on inference rather than training. I specialize in: Agentic AI & Orchestration: LangChain, LlamaIndex, AutoGen, CrewAI—building multi-agent systems that plan, act, and adapt in real time. Full-stack agent platforms combining proprietary training data, planning models, and custom actuation layers. Generative AI & LLMs: OpenAI GPT-4/API, Google Gemini, Anthropic Claude, HuggingFace Transformers. Retrieval-Augmented Generation (RAG) with vector databases (Pinecone, Chroma, Weaviate, FAISS). AI-Native Development: 42% of committed code is now AI-generated, projected to reach 65% by 2027. I don't just use AI tools—I orchestrate AI agents across the entire SDLC: planning, design, build, test, deployment, and maintenance. Deep Learning & Classical ML: TensorFlow, PyTorch, CNNs (Computer Vision), RNNs/LSTMs (Time-Series/NLP), Scikit-learn, Pandas, NumPy. Model Deployment & Optimization: Model compression, quantization, edge computing, cost-per-prediction optimization. AI Governance & Security: AI-generated code carries roughly double the security risk violations of human-written code. I implement robust governance, testing, and security controls for AI systems. **⚛️ MODERN FRONTEND** React remains the most widely used UI library, with 67% of new enterprise React projects now built on Next.js—a 300% increase since 2023. React Server Components are now the default: Core: React 19, Next.js 16 (App Router, Server Components, Turbopack), Remix, Svelte 5 (runes), Astro. Styling: Tailwind CSS, shadcn/ui (1.87M weekly downloads), Framer Motion, Material-UI. State: Zustand (35% adoption, 35ms updates) vs Redux (38% adoption, 65ms), TanStack Query, Jotai. Build Tooling: Vite 8 with Rolldown (Rust-based, 10-30x faster builds), Turbopack. TypeScript: Used by 38% of professional developers, required in 72% of frontend job postings. **📱 MODERN MOBILE** React Native's New Architecture (stable since 2024) delivers significant performance improvements through synchronous native module calls: Frameworks: React Native (Expo), NativeScript, Flutter. Native: iOS (Swift/SwiftUI), Android (Kotlin & Jetpack Compose). Emerging: GPU-powered rendering for consumer and enterprise apps. **⚙️ MODERN BACKEND & API** Runtimes: Node.js (NestJS, Express), Bun, Deno, Python (FastAPI—57.9% developer usage, up 7% from 2024), Java (Spring Boot 4.0—modularized, Java 25 LTS support). Spring AI 1.0: Built-in support for integrating LLMs and AI services into enterprise Java applications. API Design: RESTful, GraphQL (Federation), gRPC, Webhooks, WebSockets. Event-Driven: Apache Kafka, RabbitMQ, AWS SNS/SQS. **☁️ DEVOPS & CLOUD (2026 Standard)** Cloud-native and Serverless adoption has surpassed 70% penetration in enterprise IT. Multi-cloud is now the standard—Gartner projects over 75% of cloud customers will adopt this model: Cloud: AWS, GCP, Azure (multi-cloud architecture). Containerization & Orchestration: Docker, Kubernetes (K8s), Helm. Serverless: AWS Fargate, Lambda, Cloudflare Workers—extending to data pipelines, real-time streaming, and event-driven microservices. IaC: Terraform, AWS CDK, Pulumi. CI/CD: GitHub Actions, GitLab CI, ArgoCD, Jenkins. **🗄️ DATABASES & SEARCH** Relational: PostgreSQL (PostGIS), MySQL, SQLite. NoSQL: MongoDB, DynamoDB, Firebase. Vector (AI): Pinecone, Chroma, Weaviate (for RAG and semantic search). Search: Elasticsearch, Algolia, Meilisearch. Caching: Redis, Memcached. **🔗 CRM, AUTOMATION & INTEGRATION** In 2026, the CRM market is consolidating around Salesforce, Microsoft, ServiceNow, and HubSpot as a durable challenger. Both platforms have invested heavily in agentic AI, predictive intelligence, and conversational AI: CRMs: Salesforce (Apex), HubSpot (Agentic Engagement Object), Zoho. Low-Code/No-Code: Gartner forecasts the low-code market at $44.5 billion in 2026, with 75% of new enterprise apps built on low-code platforms. Automation: VBA, Excel Macros, Google App Script, Bubble.io, n8n, Make, Zapier. Citizen Development: 80% of low-code users are now "citizen developers". **🚀 Why Partner With Me in 2026?** The software industry has crossed a clear threshold in 2026. Generative AI is no longer just helping developers write code faster—it is reshaping how software is planned, built, tested, and delivered. The role of the developer has evolved from coder to curator of intent, constraints, and outcomes. **I bring:** 10+ years of battle-tested engineering across the full spectrum. Agentic AI fluency—the ability to orchestrate AI agents across the entire SDLC. Systems thinking and architectural judgment—skills that AI cannot replace. Security-first mindset—AI amplifies what's already there; where code quality is managed, AI accelerates delivery; where it isn't, it accelerates technical debt and security exposure. Whether you need an AI-native application, a microservices overhaul, an agentic workflow orchestration, or an intelligent CRM integration—I deliver professional, scalable, and governable solutions. Let's architect intelligence together. **Contact me today.**
8 years of experience in building and managing AI Systems. * I develop end-to-end AI systems from requirements analysis, and data gathering to deployment, implementing new methods/research papers, and turning projects into research outcomes. I have achieved substantial performance in DL/ML/RL models for CV and NLP domain problems. * Implementing and deploying projects handling and maintaining scalability, research papers as well as POCs. * Project planning, requirements gathering, and analysing requirements to define the system's architecture, and implementation timeline. * Provide mentoring to junior developers for ML projects. Summary: I like to work on technology that is smart, simple and sophisticated. This sums up the vast knowledge required to work on projects to excel in a working product. I like to train Deep Neural Networks and understand them well. I have mentored many students for their AI careers, teaching them Machine Learning and Mathematics. I am a mentor for the RFS (Reach for the Stars) Programme by the Aga Khan Education Board for India. I am an alumnus of this program as well. I have a cumulative experience of 8 years working in the product and service-based industry for creating Machine Learning projects. I have done some innovative work that I am proud of and am continuing to do so. I try my best to contribute my expertise to the project I am working on. Highly Experienced in Machine Learning, Deep Learning, Advanced Deep Learning, Artificial Intelligence, and Algorithms, including models in the production environment, and deploying ML models. Working with top Indian colleges like BITS, niche NLP and CV, real-estate startups, MNCs, and Fortune top 20 companies, working with sensitive anonymized datasets, and creating state-of-the-art models are some of my achievements. I have strong and correct knowledge of Deep Learning concepts from the above experiences. \- Hands-on experience across several advanced AI and graphics-related domains, including: * **3D graphics and reinforcement learning pathfinding** for autonomous driving systems, including work related to the **NASA Rover Challenge**. * **Brain tumor segmentation and classification** using computer vision and deep learning techniques. * **Video analytics and video classification**, including in-video action recognition and classification workflows.
Built and managed robust and dynamic teams in software engineering, research and development in AI and ML. With a 7-year track record of spearheading technological innovation and driving digital transformation across diverse industries, I demonstrate a unique blend of strategic vision and technical acumen. Adept at aligning technology initiatives with business objectives to foster growth and competitive advantage, I have expertise in leading cross-functional teams, optimizing technology infrastructure, and implementing cutting-edge solutions that enhance operational efficiency and customer satisfaction. Proven ability to manage large-scale projects from ideation to execution, ensuring seamless integration and maximum ROI. Exceptional communicator and leader, committed to cultivating a culture of continuous improvement and excellence.
Do you need someone that knows the ins and outs of AI, Cloud, Software Engineering, System Scaling, and Design? I'm an experienced AI Engineer, Cloud Expert, Coder, and User Experience Researcher that has worked for JPMorgan Chase, the United Nations, American Express, AT&T, and Lockheed Martin as well as for several startups and small businesses. Additionally, I've mentored people running successful startups and working in companies like Anthropic.
Software Developer. Interests: Machine Learning, BigData, Data Science, Cloud Computing. Passionate about thinking how to solve problems. Trying to give my extra-mile in every opportunity.
### About Me I am an experienced **AI and Computer Vision Specialist** with a **Master’s degree in Computer Vision** and a recipient of the **Google Inside Look 2019 Award**. My expertise lies in developing advanced solutions in **Deep Learning, Machine Learning**, and **Image Processing**, with a strong focus on building and optimizing AI-driven systems. I have successfully built AI teams using **Gemini**, **Groq**, and **Phidata**, enabling multi-agent collaboration for tasks such as **data collection, processing, and analysis**. Additionally, I specialize in **Face Recognition**, **Object Detection**, and **Video Analysis**, leveraging technologies like **TensorFlow**, **Keras**, and **OpenCV** to deliver impactful solutions. ### Key Achievements * Optimized an object detection pipeline for a startup, reducing processing time by 40%. * Built and deployed end-to-end ML models for image classification in production environments. * Guided junior developers in designing and training custom CNNs, improving team performance. ### Mentorship Philosophy I excel at breaking down complex AI concepts into digestible steps, empowering both beginners and experienced developers. Whether you're starting your journey in AI or looking to fine-tune and scale your solutions, I’m here to guide you with practical, hands-on advice. * **GitHub**: [github.com/ahmetozlu](https://github.com/ahmetozlu) * **Papers**: [Facial Expression Recognition](https://ieeexplore.ieee.org/document/8404767/) | [Automatic Age Estimation](https://ieeexplore.ieee.org/document/8404549/)
Hi, I am a Senior Data Engineer with over 6 years of experience working on Python. I have worked on Knowledge Graphs (Neo4j, Spark, NetworkX, d3.js), OS programming, creating data pipelines (Airflow, PySpark, SQL, AWS), data ingestion APIs (Dask, Azure, FastAPI, Postgres, AsyncIO) and data analysis (Pandas, Seaborn, Matplotlib). I have also created multiple courses on Udemy on High Performance Computing in Python, Exploratory Data Anaysis, Functional Programming and Scalable Data Analysis. I also answer questions regularly on StackOverflow. I am currently in Top 5% of people who answer on StackOverflow.
I have started my career in IT in the year 2006. I have worked with various technologies ranging from DBMS, Mainframes, Backend Javascript, NoSQL, Data Architecture, Cloud Computing, Machine Learning, Data Science. I have worked with multiple fortune 500 companies like IBM, TCS & Ericsson. I am currently working as a senior Machine Learning Engineer.
8+ years of experience in Machine Learning R&D with hands-on work ranging from prototyping code in academic publications to integrating solutions into production. Proficient in the entire lifecycle of a Machine Learning project, with a focus on Deep Learning applications in Computer Vision. Additional experience extends to speech, NLP, and tabular data domains. Skilled in writing clean, efficient, and scalable Python code, with a commitment of adhering to good MLOps practices.
Hi there! I can help you with: 💻 fix your code 📊 data analysis 🔎 statistical analysis for research 🔮 machine learning algorithms 🧠 artificial neural networks ➕ and more. Languages: python, R
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