Founding Engineer — AI/ML & Decision Systems

DRAGON

Website: https://dragonenterprises.co/

DRAGON sits at the intersection of design, performance, and national security.

We are building augmented-reality heads-up displays for people in motion: athletes and operators who cannot afford to look down. Our work spans wearable hardware, sport, defense, human performance, and high-motion environments.

At the center of DRAGON is a cognitive decision model: a system that takes in signals from the wearer, their environment, and their mission or performance context, then decides what information should be surfaced, when it should appear, and when it should be suppressed.

We are committed to movement: in sport, in the field, and in the country. DRAGON is built by immigrants and veterans who think differently, care deeply about craftsmanship, and believe in moving America forward.

Backed by a16z Scout. You will join at the earliest stage, where your work can directly shape the technical foundation of DRAGON.

Location:

New York, New York — remote-friendly for the right person.

Apply:

Send a note, résumé/portfolio/GitHub, and anything you’ve built, shipped, trained, modeled, or written to [email protected]

The role — Founding Engineer, AI/ML & Decision Systems

• You will help build the intelligence layer behind DRAGON: the system that turns live human, environmental, and contextual signals into real-time decisions.
• This is not a generic AI role. You will work on models and systems for high-motion environments where attention is limited, timing matters, and the wrong cue at the wrong moment can create noise instead of value.
• You will work directly with the founding team on the architecture, data pipelines, model design, and early product logic that make DRAGON more than a display.

What You May Work On

• Build and iterate on DRAGON’s cognitive decision model for real-time cue selection, timing, prioritization, and suppression
• Develop model architecture for interpreting wearer state, gaze, motion, biometrics, environmental context, and mission or performance inputs
• Design lightweight inference systems that can operate under real-world constraints: latency, bandwidth, power, noise, and limited compute
• Work with multimodal data from wearables, sensors, HUD interactions, and external systems
• Help define the data moat: what DRAGON captures, how it learns, and how the system improves across sport and defense use cases
• Prototype models for attention management, fatigue detection, route/context awareness, and decision support
• Build tooling for data collection, labeling, simulation, evaluation, and model improvement
• Work closely with hardware, product, and design to make the intelligence layer feel simple, non-distracting, and useful in motion
• Help translate athlete and operator feedback into technical requirements and model behavior
• Contribute across the stack when needed: backend, APIs, device integration, testing, dashboards, and internal tools

You Are

• A strong engineer who can move from ambiguous problem to working prototype quickly
• Comfortable with machine learning, applied AI, data pipelines, and real-world model evaluation
• Interested in human performance, wearables, AR, defense, sport, or high-stakes decision systems
• Practical about AI: you care less about demos and more about systems that work under messy real-world conditions
• Strong with Python and modern ML workflows
• Able to reason about latency, edge constraints, noisy data, and product tradeoffs
• Scrappy, fast, and comfortable building before everything is perfectly defined
• Excited to join at the ground floor and take real ownership over a core technical system

Nice to Have

• Experience with time-series modeling, sensor fusion, multimodal ML, reinforcement learning, edge AI, human-computer interaction, or real-time systems
• Experience working with wearable data, gaze/eye tracking, biometrics, IMUs, GPS, computer vision, or sports performance data
• Experience with PyTorch, TensorFlow, JAX, scikit-learn, NumPy, pandas, FastAPI, cloud infrastructure, or embedded/edge deployment
• Experience building systems with low-latency inference or constrained compute environments
• Experience in defense, aerospace, robotics, AR/VR, endurance sport, tactical systems, or human performance
• A portfolio of models, research, shipped products, open-source projects, simulations, or technical writing

Logistics

• This is an early founding team …