# Software Engineer, Machine Learning (Systems)

> Sweep360 · New York, United States · Full-time · Posted 2026-04-17

**Salary:** USD 180,000–240,000

**Workplace:** on_site

**Department:** Engineering

## Description

**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 systems quickly and decisively.
-   Communicates clearly and operates independently. 
-   U.S. Person status required (may involve export-controlled data).  
    

### Bonus if you’ve...

-   Built RF / BLE classification systems and models from zero.
-   Handled streaming systems (Kafka, pub/sub).
-   Created LLM pipelines (prompting, retrieval, evaluation).
-   Designed for adversarial or security environments.
-   Built systems that run on-device as well as in the cloud.
-   Thrived in early-stage startup environment.  
    

### What you’ll do...

-   Own system behavior and data pipelines.
-   Design ingestion **→** reasoning → decision systems.
-   Improve the decision layer for consistency and reliability.
-   Close the loop from deployments → system learning.
-   Ensure system reliability across device, cloud, and partial connectivity.
-   Partner with RF / hardware / field teams to deliver for elite users globally (~10–15% travel).  
    

### How we select...

-   Short application
-   20-minute intro call
-   Technical deep-dive
-   Practical problem discussion
-   References and offer  
    

### Final facts.

Base salary up to $240,000, depending on qualifications, experience, and impact. Total compensation includes equity, premium insurance, 401(k), flexible PTO, and other individual benefits.  
  
You’ll join us on-site at our HQ in New York City with occasional domestic and global deployments.  
**Apply. Make history. Build humanity’s defense against machines.**

## Apply

[Apply at Sweep360](https://apply.workable.com/sweep360/j/AAA5C518FA/apply)

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