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🚀 AI & SaaS Development From Idea to Working Product I'm Johnson, a full-stack AI developer and SaaS architect helping founders, startups, and businesses turn ideas into practical, working software. I specialize in building AI-powered applications, SaaS MVPs, automation tools, dashboards, and full-stack web platforms using modern technologies across the frontend, backend, database, AI, and deployment layers. I'm also the sole founder of Useralph, an AI-powered vehicle checking platform that uses RAG pipelines and LLM analysis to process vehicle history and salvage data. 💡 What I Build AI & SaaS Development • AI-powered web applications • OpenAI and LLM integrations • RAG pipelines and document-based AI assistants • Chatbots and agent-style workflows • AI automation and workflow tools • SaaS MVPs from concept to launch Full-Stack Development • React, Next.js, TypeScript, Tailwind CSS • Python, FastAPI, Django • Node.js and Nest.js • PostgreSQL, Supabase, Firebase, Redis • REST APIs, GraphQL, and WebSockets • Authentication, roles, databases, and dashboards • Deployment with Vercel, Docker, and cloud platforms 🛠️ Product Development I work across the entire product stack, so you don't need to coordinate multiple developers just to get your MVP built. I can help with: • Product architecture and technical planning • Frontend and responsive UI development • Backend APIs and business logic • AI/API integrations • Authentication and multi-user systems • Admin dashboards and internal tools • Database design and integrations • Automation workflows • Deployment and production setup 🧠 How I Work I believe good development starts with understanding the product—not immediately writing code. Before development begins, I help define the core requirements, choose the right technology stack, and avoid unnecessary complexity. From there, I build the first version with clean architecture and a clear path for future improvements. My approach is: • Clear scope and technical direction • Fast, structured MVP development • Practical technology choices • Regular progress updates • Maintainable and scalable code • Product-focused problem solving The goal is to get you from idea → working product → real users without overengineering the first version. 🎯 A Good Fit If You Need • An AI developer who also understands full-stack development • A SaaS developer who can handle frontend and backend • An experienced Python, FastAPI, Node.js, or React developer • An AI/API integration specialist • Someone to turn a rough idea into a working MVP • A technical partner who can help shape the product as well as build it I work best with founders, startups, and businesses that value clear communication, practical solutions, and steady execution. ✨ Let's Build Your Product Whether you're starting with an idea, improving an existing application, or looking to add AI and automation to your product, I can help take it from concept to a working solution. Send me your requirements and let's discuss the best way to build it.

I'm a Junior Artificial Intelligence Engineer with a strong foundation in Machine Learning, Deep Learning, Natural Language Processing (NLP), and Computer Vision. I am committed to transforming data into intelligent solutions that address real-world challenges. In my early career, I've gained valuable experience working on a range of projects, from developing diagnostic tools for medical imaging to creating NLP models for language translation and sentiment analysis. My focus is on building and contributing to AI systems that solve complex problems and drive innovation. My technical expertise includes: Machine Learning: Skilled in building predictive models, optimizing algorithms, and deploying scalable solutions. Deep Learning: Proficient in designing and training neural networks for tasks like image recognition, object detection, and speech processing. Natural Language Processing (NLP): Experienced in developing models for text classification, translation, sentiment analysis, and more. Computer Vision: Expert in image processing, image recognition, image segmentation, and object detection with hands-on experience in using YOLO, TensorFlow, and OpenCV. Whether you're looking to develop a cutting-edge AI application, enhance your existing systems, or explore new AI-driven opportunities, I'm here to help. I'm dedicated to delivering high-quality, impactful solutions that align with your goals. Let’s connect and explore how I can contribute to your next project!

Have an AI project that needs to actually work in production, not just look good in a demo? I'd love to hear about it. I architect the kind of AI systems that teams rely on every day: autonomous agents that run your operations, RAG pipelines that give you real answers from your own data, voice interfaces that handle client intake in real time, and AI video and content engines that produce at scale. My clients span tech, legal, finance, medical, and media, and what connects them is a need for AI that performs reliably under real constraints. What I Build: Autonomous Agents & Multi-Agent Orchestration Stateful AI agents with conditional routing, graph-based workflows (LangGraph), and tool-calling architectures designed for production workloads. I build with safety and governance from day one: human approval loops, strict compliance guardrails (HIPAA/COPPA), and containerized execution to keep your agents predictable and under control. Whether you're inspired by what you've seen from OpenClaw or need something more controlled and enterprise-ready, I can help you architect the right solution. Example: a Clinical Dispatch Agent handling patient intake, lead qualification, and live CRM updates end-to-end. High-Fidelity RAG & Context Engineering Beyond basic vector search. I apply context engineering and advanced prompt engineering techniques including metadata filtering, vertical slicing, and structured retrieval to maximize signal and minimize hallucination. I work with vector databases like Pinecone, Qdrant, and pgvector alongside Supabase and PostgreSQL for hybrid storage. The goal is audit-grade precision, not "good enough" answers. Example: a GovTech Opportunity Analyzer on AWS that synthesizes federal contract requirements with high accuracy. Real-Time Voice & Multi-Modal AI Low-latency voice and vision interfaces built on Retell AI, LiveKit, Twilio, ElevenLabs, Deepgram, and Gemini. I handle the full stack from speech-to-text through intent processing to response generation, deployed on infrastructure like Next.js, Vercel, and Supabase for fast, reliable performance. Example: a 3D voice-powered learning companion for children featuring real-time adaptive mentoring, long-term memory, and COPPA-compliant safety, architected from zero to production. AI-Powered Video & Content Pipelines End-to-end content automation that orchestrates across the current generation of models (Kling, Sora, Veo, LTX-2, HeyGen, WaveSpeed), routing each task to the right model based on quality, cost, and use case. My pipelines handle everything from web scraping and script generation to video sourcing, voice synthesis (ElevenLabs, Amazon Transcribe, Nvidia Parakeet), and brand-consistent output at scale. Example: a video engine serving 50+ publishers, automating metadata and production for 1,000+ assets monthly. How I Work: I use Claude Code, Codex, OpenCode, and Cursor alongside agentic development workflows to ship robust systems faster than traditional development, with the engineering judgment to know when to trust AI output and when to rewrite it. I bring the same ownership mindset to client projects that I bring to building my own products from zero to production. My core stack is Python, TypeScript, FastAPI, Next.js, React, and Node.js, with infrastructure across GCP, AWS, Vercel, and on-premise deployments for clients who need data to stay on their own hardware. Sound like a fit for what you're working on? Drop me a message with a quick overview of your project and I'll get back to you promptly.

-- Top 3% of AI Developers on Upwork (rated: Top Rated Plus) -- 5+ Years of Professional Experience in Machine Learning -- Specialized in Generative AI, Image Generation, and Speech Generation As a specialist in AI, I bring a strong theoretical foundation alongside practical expertise in machine learning, deep learning, and generative AI models. With over 5 years of experience, I excel in applying advanced AI techniques to solve complex problems in image generation, speech synthesis, and more. Key Areas of Expertise: - Deep expertise in generative AI models for image, video, and speech generation (GANs, VAEs, diffusion models). - Skilled in designing and fine-tuning LLMs and multimodal models, integrating image, text, and speech for advanced AI solutions. - Proficient in the full ML/DL pipeline: architecture design, model training, deployment, and continuous optimization. - Extensive experience in applying cutting-edge neural networks for computer vision, NLP, and audio processing. - Developed custom generative models for use cases including text-to-image, image-to-image, speech-to-text, text-to-speech, and voice cloning. - Implemented solutions for automated content generation, image captioning, visual understanding, speech synthesis, and multimodal fusion. - Focused on optimizing models for deployment on mobile, cloud, and edge devices using tools like PyTorch, TensorFlow, and NVIDIA frameworks. Research Experience: - Published work in reinforcement learning at ICML ("Inverse Constrained Reinforcement Learning") with applications in human feedback for improving generative models. - Expertise in Reinforcement Learning from Human Feedback (RLHF), a key technique used in training high-performance LLMs and generative models. Technical Skills: - Core Areas: Generative AI, Image Generation, Speech Generation, Multimodal AI, Computer Vision, NLP, OCR, Large Language Models, Big Data Analytics. - Libraries/Frameworks: TensorFlow, Keras, PyTorch, Hugging Face, OpenAI, CoreML, FastAPI, Flask. - Toolkits: PyTorch, Numpy, Pandas, CUDA, TensorFlow, OpenCV, Tflite. - Operational Tools: GCP, AWS, Kubernetes, Docker, Github, Gitlab.

Looking for a Data Scientist to build, fix, or scale high-performance Python systems? I design custom, production-ready AI systems and robust backend architectures that deliver real business growth. I don't treat AI as a black box. Because I have built core machine learning and deep learning algorithms completely from scratch using raw mathematics and fundamental code, I understand exactly how models make decisions under the hood. During development, I actively inspect and visualize internal neurons and variables to make sure your model is truly learning—not just making lucky guesses, overfitting, or failing silently when introduced to real-world users. When pre-packaged tools break, give wrong answers, or hit performance ceilings, this deep understanding allows me to diagnose problems at the root level and build custom solutions. Where standard black-box developers hit a wall, I combine mathematical rigor with clean, scalable Python code to keep your project moving forward. ⚡ Core Capabilities - AI, LLMs & Generative Systems: Custom AI agents, smart search & RAG pipelines, research paper implementation, model fine-tuning, PyTorch/TensorFlow deployments, and deep model debugging. - Python Backend Architecture: Scalable APIs (FastAPI, Django), vector databases, and cloud infrastructure. - Quantitative Trading Systems: Automated trading bots, custom backtesting engines, and exchange API integrations. Ready to build an AI system that actually delivers results? Click "Invite to Job" to discuss your project. Technologies: Python | PyTorch | TensorFlow | Scikit-learn | Data Science | Deep Learning | Machine Learning | AI Engineer | LLM | RAG | AI Agents | LangChain | Vector Databases | Quantitative Trading | Algorithmic Trading | Trading Bot | Backtesting | VectorBT | Time Series | FastAPI | Django | AsyncIO | Celery | Redis | PostgreSQL | Docker | AWS | GCP | REST APIs | Microservices.

🚀 🥇 Expert-Vetted | Hands-On AI/ML Engineer | I Build LLM Apps, RAG Systems & AI Agents (MCP, LangGraph) | Python, AWS, GCP, Azure | Healthcare & FinTech 👁‍🗨 Overview I build and ship production AI systems myself, end to end. No handoffs, no delegation: I design the architecture, write the code, and stay on it until it is deployed, monitored, and generating ROI. I bring 15+ years of hands-on AI/ML engineering, a PhD in Machine Learning from Iowa State University, and a Master's in Computational Neuroscience from UC San Diego. ✅ What I Build: • LLM Applications: RAG pipelines, chatbots and copilots, document AI, semantic search, structured data extraction • AI Agents: Multi-agent systems, MCP (Model Context Protocol) tool integrations, LangGraph orchestration, function/tool calling, agentic workflow automation • Model Customization: Fine-tuning (LoRA/QLoRA, RLHF/DPO), prompt optimization, evals and guardrails, open-weight model serving (vLLM) • Healthcare AI: Clinical trial automation, medical document generation, HIPAA-compliant systems • Full-Stack AI Products: Python/FastAPI backends, React frontends, Kubernetes, CI/CD across AWS, GCP, Azure 🎯 Recent Hands-On Builds: • Engineered a clinical trial intelligence system for enterprise pharma: ingested, embedded, and indexed 100K+ trials with multi-index, multi-LLM RAG and advanced PDF parsing, powering Q&A, chat, and benchmarking • Built a GenAI product that drafts 100+ page regulatory clinical trial protocols (95% of the full M11 document), with multi-agent validation, consistency, and styling checks • Coded and deployed an ICD-10 billing code prediction model on GCP and an EHR-integrated physician sidebar on AWS EKS • Rescued a failing third-party ML platform, refactored it, and took it to production on AWS at ResMed (NYSE: RMD), enabling their first commercial AI healthcare product • Built ML-powered ad targeting and recommendation systems generating $100K+/month, plus AI products earning $1M+ revenue in year one 💼 Industry Expertise: • Healthcare/Pharma: Clinical trials, EHR API integration, medical AI, FDA-regulated software • FinTech: Real-time fraud detection, card-linked platforms, transactional APIs (MasterCard and Visa partnerships) • Enterprise SaaS and Retail/E-commerce: Multi-tenant APIs, recommendation engines, customer analytics 🔧 Technical Stack: AI/ML: GPT-5, Claude, Gemini, Llama, DeepSeek, Qwen; fine-tuning (LoRA/QLoRA, PEFT, RLHF/DPO); RAG and GraphRAG, hybrid search, rerankers, embeddings Agents: MCP, LangGraph, LangChain, LlamaIndex, CrewAI, OpenAI Agents SDK, structured outputs, tool calling Languages: Python, TypeScript/JavaScript, SQL, Java, Go Frameworks: PyTorch, Hugging Face, FastAPI, React, TensorFlow, Scikit-learn Serving & MLOps: vLLM, Ollama, AWS (SageMaker, Lambda, ECS/EKS), GCP (Vertex AI), Azure AI Foundry, Kubernetes, Docker, MLflow, Weights & Biases Evals & Observability: LangSmith, Langfuse, RAGAS, guardrails, LLM cost optimization Databases: PostgreSQL/pgvector, Pinecone, Qdrant, Weaviate, ChromaDB, Elasticsearch, MongoDB, Redis 📊 Quantifiable Impact: • 100K+ clinical trials processed, indexed, and made queryable for enterprise users • 100+ page medical documents generated with regulatory compliance • 94% accuracy in crisis detection and 73% engagement increase for a nonprofit youth chatbot • 10X subscriber growth driven by models I built and deployed • $100K+/month revenue from ML-powered ad targeting 🎓 Credentials: • PhD, Machine Learning (Iowa State University); M.Sci., Computational Neuroscience (UC San Diego) • IBM Certified: RAG and Agentic AI; Deep Learning Specialization (Coursera) • Published AI/ML researcher (Psychological Science, ICSE); 4 provisional patents in AI/computer vision 🌟 What Sets Me Apart: I am senior, and I still write the code. On every engagement you get one engineer doing the actual work: architecting, coding, testing, deploying, documenting. Because I have built AI in regulated healthcare and fintech environments, compliance, evals, and monitoring are baked in from day one rather than bolted on. My neuroscience background shapes how I build AI systems that genuinely understand human behavior and needs. 🤝 Working With Me: You work directly with me, and I personally do the work. Expect working code early (usually in the first week), frequent demos, clear async communication, and clean documentation at handover. US-based in San Diego (Pacific time), available for both short sprints and long-term builds. Have an AI feature or product that needs to get built? Send me the details and I will reply with exactly how I would build it.