Cameron Malone — founder of Malone Technologies LLC. Building intelligent systems at the intersection of AI, embedded hardware, robotics, power systems, and cybersecurity. From microcontrollers with 100KB of RAM to 200B-parameter model fine-tuning.
I build systems that bridge the full depth of engineering — from bare-metal firmware and custom PCB design to deep reinforcement learning research and GPU-accelerated AI pipelines. My work spans electrical engineering, computer engineering, computer science, robotics, and machine learning, often on the same project.
My master's thesis develops a dual-purpose reinforcement learning agent capable of both energy management and cybersecurity defense for microgrids — an autonomous system that controls power distribution while simultaneously detecting, defending against, and responding to cyberattacks in real time.
Advancing the state of the art in reinforcement learning, embedded AI, cybersecurity, and power systems through rigorous applied research. From novel RL architectures to hardware-in-the-loop training environments, we push boundaries and publish results.
Deep technical advisory for organizations navigating complex engineering challenges in AI/ML, embedded systems, IoT infrastructure, edge computing, and cyber-physical systems. Cross-domain expertise that bridges hardware and software.
End-to-end engineering execution. We design, build, and deliver production-grade systems — from embedded firmware and networking protocols to AI agent platforms and full-stack training pipelines.
Custom model creation, training, and fine-tuning tailored to your data and use case. Our multi-node infrastructure supports independent training across dedicated GPU systems — from full fine-tuning up to 70B parameters to QLoRA/quantized fine-tuning up to 200B parameters. LLMs, vision models, diffusion models, and domain-specific architectures.
A complete, production-ready implementation of the Tailscale protocol for ESP32 microcontrollers. Built in C and Assembly with full ts2021 protocol support, WireGuard encryption (ChaCha20-Poly1305), DISCO path discovery, DERP relay, and STUN — memory-optimized to ~100KB SRAM.
View on GitHub →A 4B parameter language model purpose-built for finance and accounting, achieving a 97% accuracy rating. Trained on a custom-generated dataset and paired with a bespoke AI tooling framework for end-to-end financial analysis, tax preparation, and accounting automation.
An RL training and evaluation environment for microgrid energy management systems. Bridges simulation and real hardware, enabling agents to train and validate against realistic microgrid dynamics using IoT hardware-in-the-loop.
Research on augmenting PPO with attention mechanisms for improved anomaly detection. Explores how attention layers enhance an RL agent's ability to identify and respond to anomalous patterns in high-dimensional operational data.
A hardware-in-the-loop RL platform using real IoT devices for training energy management systems. Bridges the sim-to-real gap with actual sensor data, real power measurements, and physical system dynamics.
A custom communications library for PyTorch supporting distributed and parallel computing workflows for AI/ML training and inference pipelines.
Comprehensive RL training framework paired with a native C library for ESP32 deployment. GPU-accelerated training to microcontroller inference.
A locally-hosted AI assistant and autonomous agent platform featuring multi-PC orchestration, full computer control, and autonomous agent execution. Includes 3D model generation, image generation, audio synthesis, and video generation — all running on local hardware without cloud dependencies.
A remote desktop streaming application built in Rust. H.264/H.265 adaptive bitrate video, Opus audio, Tailscale integration with auto-peer auth, OTP access, mDNS discovery, bidirectional clipboard sync, file transfer, and cross-platform support — all in a single unified binary.
I love hard problems. I love complexity. I love the moment when a system that spans five engineering disciplines clicks into place and works — and I love the grind it takes to get there.
I've spent years building across the full stack of engineering — implementing the Tailscale protocol from scratch in C for a microcontroller with 100KB of RAM, designing RL agents that autonomously defend power grids from cyberattacks, training billion-parameter language models on custom datasets. Every domain I've entered has deepened my ability to solve problems in the others. Electrical engineering, computer engineering, machine learning, embedded systems, cybersecurity, robotics, graphics programming — I went deep in all of them because that's where the most interesting problems live: at the boundaries.
Complexity doesn't intimidate me. It motivates me. Every new challenge is an opportunity to sharpen my skills and expand what I'm capable of. I've built my career around the belief that the most impactful engineering happens when you refuse to stay in one lane.
Malone Technologies LLC is a single-member limited liability company registered in the State of Tennessee, United States. We provide consulting, custom engineering, AI/ML model development, embedded systems, and cybersecurity services to business clients on a contract basis. We do not sell physical goods or subscription products.
For invoice questions, project-status inquiries, technical support on delivered work, billing disputes, or any other matter, contact:
Email: cameron@malone-technologies.com
Response time: within two (2) business days, Monday–Friday, 9am–6pm Central Time.
Mailing address available on request for formal correspondence.
All engagements are priced per scope of work agreed in writing before work begins. Invoices are issued in U.S. Dollars through Stripe and are due within fourteen (14) days of issue unless a different term is stated on the invoice. Payment methods accepted: credit/debit card, ACH, wire transfer, and paper check. Late payments may accrue interest at 1.5% per month or the maximum rate permitted by Tennessee law, whichever is lower.
Because Malone Technologies LLC delivers customized professional services rather than off-the-shelf products, refund eligibility depends on whether work has been performed:
If you dispute a charge, please contact us directly first — most disputes are resolved faster through email than through a card chargeback. Refunds issued via Stripe are returned to the original payment method and typically appear within 5–10 business days.
Either party may terminate an ongoing engagement with seven (7) days written notice via email. Upon cancellation, Malone Technologies LLC will deliver all work in progress at the current milestone and invoice the client for any unpaid time or deliverables completed up to the cancellation date. Any prepaid amount beyond completed work is refunded per the Refund Policy above.
By engaging Malone Technologies LLC, the client agrees that:
Malone Technologies LLC collects only the information needed to deliver services and process payments: name, email, business name, billing address, and project-related communications. Payment card data is handled exclusively by Stripe and never stored on our systems. We do not sell, rent, or share client data with third parties. Client data is retained for the duration of the engagement plus seven (7) years for tax and legal-record purposes, then destroyed. To request a copy or deletion of your data, email cameron@malone-technologies.com.
Our cybersecurity and AI services may be subject to U.S. export-control regulations (EAR, ITAR) depending on the specific engagement. We do not provide services to individuals or entities located in countries or on lists sanctioned by the U.S. government (OFAC SDN list, entity lists, embargoed nations). Clients are responsible for complying with their local laws regarding any technology or services received.
Policies last updated: April 23, 2026. These policies may be updated from time to time; material changes will be posted to this page with a revised date. Continued engagement after policy changes constitutes acceptance.