Technical Co-Founder / Founding CTO

This is not a senior engineer role with co-founder branding attached. This is the real thing. You will be the technical mind of the company - the person who makes foundational architecture decisions, owns the hardware roadmap, and determines how an early-stage platform becomes a product that survives contact with industrial environments.

The business co-founder covers business strategy, go-to-market, customer discovery, and fundraising. You own everything technical - architecture, toolchain, and technical hiring as the company grows. You will hold meaningful co-founder equity and shape the direction of the company from day one.

If you have ever wanted to build something genuinely new - a system that lives at the intersection of embedded hardware, machine learning, and industrial AI, at a moment when all three are converging - this is that opportunity., You will own the full edge AI stack - from raw sensor signal to intelligent on-device output - and every layer in between:

· Hardware architecture: Define and evolve the sensor hardware stack - MCU selection, sensor modalities, enclosure requirements, and the hardware roadmap from current prototype to production-grade product.

· Embedded intelligence: Develop firmware for real-time signal acquisition and on-device ML inference - the core of what makes this product work without cloud.

· ML pipeline: Own data collection, model design, quantization, and deployment to edge hardware - building a system that learns from real industrial environments.

· Edge AI platform: Extend and productize the existing software platform - the diagnostic intelligence layer that turns sensor data into prescriptive maintenance guidance.

· Certification and scale: Drive the hardware certification strategy (CE, FCC, relevant industrial standards) and define the architecture that scales from single-asset deployments to full industrial facilities.

· Production embedded development in C/C++: Production-grade industrial microcontrollers - ARM Cortex-M class hardware. You have taken a design from bring-up through manufacturing. Dev board experience alone is not sufficient.

· Signal processing: FFT, spectral feature extraction, vibration analysis from MEMS accelerometers and IMUs. You know what a vibration signature tells you and how to extract meaningful features from noisy real-world data.

· Embedded ML / TinyML: You have deployed quantized models on resource-constrained hardware. You understand the trade-offs between model size, inference latency, and accuracy at the edge.

· Software ownership: You can independently own, extend, and refactor a production-grade software codebase. This is full-stack technical responsibility, not feature work.

· Embedded Linux and edge compute: Hands-on experience with NVIDIA Jetson-class or equivalent edge GPU compute platforms for the gateway layer., · Schematic capture and layout for mixed-signal sensor hardware. You have designed boards and had them manufactured - not just assembled reference designs.

· Experience shipping a certified industrial IoT or industrial automation product (CE, FCC, UL, IEC 61508 awareness)

· Background in condition monitoring, predictive maintenance, or vibration analysis in an industrial context

· Familiarity with industrial automation equipment and the environments it operates in

· Experience with on-device / local LLM inference on constrained edge hardware

· Knowledge of industrial communication protocols - Modbus, OPC-UA, EtherCAT

· Experience raising a seed or pre-seed round alongside a technical product, Bachelor’s degree minimum in Electrical Engineering, Mechatronics, Robotics, Computer Engineering, or a closely related field. Master’s or PhD in condition monitoring, structural health monitoring, signal processing, or embedded systems is a strong plus - but demonstrated shipped product experience outweighs academic credentials at this stage., 4-10 years of relevant industry experience. We are looking for someone who has shipped real hardware into real environments - not exclusively academic or hobbyist projects. The most relevant backgrounds are industrial automation, industrial IoT hardware startups that have completed a full product cycle, or embedded systems companies operating in regulated or harsh-environment industries., · You are primarily a data scientist or cloud software engineer without hands-on hardware and firmware experience

· You are looking for a senior engineering salary at this stage rather than an equity-first co-founder arrangement

· You want to implement someone else’s technical vision rather than own your own

· Co-founder equity: Meaningful stake, negotiable based on contribution and timing. You are a founder, not an employee.

· Full technical ownership: Architecture, toolchain, hiring - all yours. No committee, no legacy constraints.

· Authorship: Your name will be on this. The architecture you design, the technical decisions you make, the product you ship - these will define what Axon Logic is.

· A category-defining problem: The convergence of AI, embedded ML, and industrial intelligence is happening now. You will be building at the center of it.

For the past decade, AI rewired the software world. Search, language, vision, code - entire industries were transformed from the inside out. The models got smarter, the infrastructure got faster, and a generation of software companies was built on the back of that shift.

The next transformation is different. It is not about what AI can do on a server. It is about what AI can do in the physical world - on the factory floor, inside the machine, at the point where silicon meets steel.

“The next wave of AI is Physical AI.”- Jensen Huang, CEO, NVIDIA

Physical AI is already reshaping industrial operations at their foundation. For decades, industrial machinery has operated largely in the dark - generating vast amounts of physical data that no system could interpret fast enough, locally enough, or intelligently enough to matter. That is changing. Embedded intelligence is moving onto the machines themselves: detecting what human senses cannot perceive, diagnosing what years of experience alone cannot explain, and prescribing action before a failure becomes a crisis.

Axon Logic is building at the center of this shift. The software wave created extraordinary companies - the physical wave is just beginning. This is where that work starts., We are building the product this industry has been waiting for.

For decades, industrial machinery has been the last frontier untouched by real intelligence. Factories generate enormous amounts of data from their equipment every second - and almost none of it becomes actionable knowledge. The result is over $1 trillion in unplanned downtime every year, and a growing gap between the intelligence the industry needs and what it actually has.

The technology to close that gap simply did not exist - not at the right cost, the right size, or the right level of intelligence. It does now.