Mike S.

AI can move a project forward fast. It can also create architecture nobody trusts, firmware that almost works, security holes no one noticed, ML models that don’t survive real data, and prototypes that fail the moment they touch real hardware. That is where I create the most value. I help founders, inventors, and technical teams use AI aggressively without letting AI-generated mistakes turn into expensive engineering debt. If you are already using ChatGPT, Claude, Cursor, Codex, Replit, Lovable, or other AI tools, but your project is getting stuck because the output is brittle, insecure, poorly specified, hard to validate, or disconnected from real-world constraints, I can help. Think of me as an AI engineering whisperer: someone who understands both the power of AI and the engineering realities that AI often misses. My strongest fit is not commodity implementation. If your project is fully specified and just needs code written, there are many lower-cost options on Upwork. My value is highest when the system is ambiguous, partially built, AI-generated, technically risky, or crossing the boundary between software, hardware, firmware, data, ML, and operations. I help answer questions like: ▸ Is this AI-generated architecture actually safe to build on? ▸ Will this prototype survive real users, real hardware, real timing, and real edge cases? ▸ Are there hidden security, reliability, integration, or model-validation risks? ▸ What should be rebuilt, what should be kept, and what should be tested first? ▸ How do we turn a promising AI-assisted prototype into a real engineering system? MY WORK TYPICALLY FALLS INTO FOUR AREAS: AI ENGINEERING RESCUE ▸ Review AI-generated code, architecture, workflows, and product plans ▸ Identify brittle assumptions, missing tests, security gaps, and failure modes ▸ Turn prototype chaos into a coherent technical path REAL-WORLD SYSTEM ARCHITECTURE ▸ Design systems that work beyond the demo ▸ Bridge AI, software, hardware, firmware, sensors, wireless links, and operations ▸ Translate unclear product ideas into buildable technical specifications APPLIED ML & DECISION SYSTEMS ▸ Build and validate machine-learning models for noisy, real-world decision environments ▸ Work with time-series data, feature engineering, model evaluation, and out-of-sample testing ▸ Identify leakage, overfitting, regime-change problems, and weak validation methods ▸ Develop ML systems where bad assumptions create real financial or operational consequences EMBEDDED, IOT & HARDWARE-AWARE DEVELOPMENT ▸ Firmware, PCB, sensor, wireless, and real-time system review ▸ STM32, ESP32, Raspberry Pi, BLE, cellular, IoT, industrial, and prototype systems ▸ Debug issues where software assumptions collide with hardware reality I have taken numerous products from concept to production, including embedded systems, IoT devices, industrial controls, data systems, automation tools, and AI-enabled workflows. I also build applied ML models for noisy, high-stakes decision environments, including financial market models that I use in my own trading. That work demands strict leakage control, disciplined feature engineering, out-of-sample validation, model-failure analysis, and constant attention to whether a signal is real or just noise. My background includes MSEE-level engineering training, decades of hands-on product development, and extensive practical use of LLMs, agentic AI workflows, and applied machine learning. Most AI consultants do not understand hardware. Most hardware engineers underuse AI. Most ML prototypes are not tested hard enough against real-world failure modes. I bridge those gaps. Best fit for: ▸ Founders building AI-assisted products ▸ Teams with prototypes that work in demos but not in the real world ▸ Companies using AI-generated code and needing review, hardening, or architecture cleanup ▸ Teams building ML, forecasting, automation, or decision-support systems ▸ Embedded, IoT, robotics, sensor, wireless, or firmware projects where AI alone is not enough ▸ Inventors who need a senior technical reality check before spending serious money The value I bring is practical technical judgment. I help you move faster without fooling yourself. A short review can often prevent weeks or months of wrong-direction development. Relevant technical areas: Embedded systems • AI/ML systems • LLM workflows • Agentic AI • System architecture • Applied machine learning • Time-series modeling • Forecasting • IoT • Firmware • PCB design • STM32 • ESP32 • Raspberry Pi • BLE • Cellular IoT • Real-time systems • Sensors • Wireless systems • Product development • Prototyping • Manufacturing readiness • Security review • Automation • Data pipelines • Python • C/C++