Software Engineer, Machine Learning (Systems)

About this role

TL;DR — We’re building humanity’s defense layer for the AI age and are looking for an exceptional ML engineer to stabilize the system that turns raw signal into decisions — across device, cloud, and offline environments.

*If you would have joined early Tesla to make Autopilot work in the real world and improve across the fleet — this is that role.*

### Why Sweep?

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.

### What makes this role special?

• First dedicated ML systems hire.
• You’re the difference between a system that exists and one that works.
• Make the system reliable under pressure — data, pipelines, and decision logic.
• Take outputs from sensing systems and turn them into consistent, trusted decisions.
• Define how inference works when inputs are incomplete, noisy, or conflicting.
• Your work is used in high-stakes environments where outputs must be trusted.
• Gain pre-Series A ownership as one of the first 10 engineers.

### What we’re looking for...

• 5–10 years building and operating production systems
• Strong system design across APIs, pipelines, and data storage
• Deployed ML / LLM systems in production and improved them via feedback loops
• Strong Python, plus Go/TypeScript (or similar)
• Comfortable working across device and cloud environments.
• Able to debug production s...