# RF / Wireless Systems Engineer

> Sweep360 · New York, United States · Full-time · Posted 2026-04-06

**Salary:** USD 160,000–240,000

**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 RF/signals engineer to turn noisy wireless signals into reliable, actionable intelligence.**

_If you would have joined Palantir, Nest, or Tesla at the very early start to build an infrastructure from scratch — not just clean datasets — 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 RF / signal intelligence hire.
-   You’ll define how the system interprets signals — from raw input to device-level intelligence.
-   There is no clean dataset or ground truth — you determine what the signal means.
-   Work across BLE, Wi-Fi, timing, and behavioral patterns to infer what isn’t explicitly visible.
-   Solve signal problems directly with hardware and deployments as they emerge.
-   Your output is used immediately in environments where signal is incomplete and decisions still have to be made.
-   Gain pre-Series A ownership as one of the first 10 engineers.  
    

### What we’re looking for...

-   3–7 years working with wireless systems, signal processing, or applied ML.
-   Deep understanding of BLE, Wi-Fi, RF behavior (advertising, beacons, probes, noise).
-   Ability to infer device type or behavior from incomplete or obfuscated signals.
-   Strong Python and familiarity with ML techniques (PyTorch, NumPy, etc.)
-   Comfortable experimenting with unconventional approaches (e.g. signal transformations, feature extraction, data fusion) and shipping what works.
-   Ships under pressure — not just research.
-   U.S. Person status required (may involve export-controlled data).  
    

### Bonus if you’ve...

-   Built RF / BLE classification systems and models from zero.
-   Classified unknown devices despite modern device identification challenges (e.g. MAC randomization, ephemeral identifiers, obfuscated broadcasts).
-   Worked on adversarial / security problems.
-   Built inference systems without labeled data.
-   Worked closely with hardware teams.
-   Operated outside controlled environments (not just offline pipelines).
-   Demonstrated unconventional problem-solving in adversarial or complex environments.

### What you’ll do...

-   Turn raw signal into device-level intelligence.
-   Classify devices without explicit identifiers.
-   Detect anomalies and suspicious behavior patterns.
-   Improve precision and reduce false positives in real time.
-   Use field data from deployments to continuously improve system performance.
-   Turn incomplete signals into product capability.
-   Deploy globally to validate your work (~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/22F6E04A71/apply)

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