Machine Learning Engineer
About The Position
We’re building humanity’s defense layer for the AI age and are looking for an exceptional machine learning engineer to build the AI decision system that turns raw signals into trusted operational decisions across device, cloud, and offline environments. This role is akin to joining early Tesla to make Autopilot work in the real world and improve across the fleet, or Figure AI before humanoids left the lab to build the firmware that made them trustworthy. As intelligent machines proliferate into every part of the physical world, we humans still lack a defense layer to ensure the systems and devices we rely on remain aligned with us. We’re building that layer today by deploying alongside the world’s highest-stakes teams — Olympic delegations, F1 paddocks, halftime shows, global tours, studio productions, senior government officials, and executive protection units. What we learn there becomes the foundation for a civilization-defining capability. We’re a small, talent-dense team with high ownership, high velocity, and low ego. We care deeply, move fast, and are here to build something that outlasts us. Together, we’ll redefine cyber-physical security for the AI age.
Requirements
- 5–10 years owning production systems end-to-end.
- Strong system design across APIs, pipelines, and data storage.
- Built production AI systems trusted in real-world operations.
- Strong Python, plus Go/TypeScript (or similar).
- Comfortable building systems spanning edge devices, cloud, and intermittent connectivity.
- Able to debug production systems quickly and decisively.
- Communicates clearly and operates independently.
- U.S. Person status required (may involve export-controlled data).
Nice To Haves
- Handled streaming systems (Kafka, pub/sub).
- Created production LLM or inference pipelines (prompting, retrieval, evaluation).
- Designed for adversarial or security environments.
- Built systems that run on-device as well as in the cloud.
- Thrived in an early-stage startup environment.
Responsibilities
- Ensure reliability of the entire AI system—from data ingestion to operator decision.
- Turn noisy cyber-physical observations into trusted operational decisions.
- Define how the system reasons under uncertainty.
- Shape how the production AI system behaves in the real world.
- Design ingestion → reasoning → decision systems.
- Drive inference reliability, predictable logic, and transparent reasoning.
- Close the loop from deployments → system learning.
- Make the system trusted under real-world conditions.
- Partner with RF / hardware / field teams to deliver for elite users globally (~10–15% travel).
Benefits
- Total compensation includes equity, premium insurance, 401(k), flexible PTO, and other individual benefits.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
