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EI
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Canada
- $160,000 to $180,000 CAD / year
- Full-time
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Added just now
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- $80,000 to $90,000 CAD / year
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Added 14 mins ago
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Machine Learning Engineer
AgileGrid Solutions
Canada
- Full-time
We are seeking a talented and driven Machine Learning Engineer to join the Qualcomm AI Processor Solutions team. This role offers an exciting opportunity to contribute to the development of…
Added 15 mins ago
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Tunnel Engineer
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Toronto, ON
- $95,000 to $115,000 CAD / year
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BG
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- $50,000 to $65,000 CAD / year
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Added 15 mins ago
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Added 30 mins ago
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Open People Network (OPN)

RF Systems Engineer

Toronto, ON, Canada
Greater Toronto Area, Canada, Canada

Full-time

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Job details

Job type: Full-time
Apply by: Oct 23, 2026
Posting language: English
Posted: Jul 30, 2026

Original job description

Osprey Systems is building Canada’s sovereign counter-drone capability. Our distributed detection and interception system is designed for the environments where everything else fails: extreme cold, GPS-denied, and network-degraded conditions. We serve critical infrastructure operators and defense customers with a single product line, built in Canada.

We are a small founding team backed by a clear funding pathway through Canadian defense innovation programs and paid civilian deployments. This role is our first engineering hire, and the person in it will define the RF detection capability that anchors our entire product.

The role

Drones announce themselves over radio before they are ever seen or heard. Your job is to catch that signal, identify it, and separate it from everything else on the air, in real time, on a low-power node sitting outdoors in a Canadian winter.

You will own the RF detection layer end to end: architecture, software-defined radio integration, signal detection and protocol identification, and the pipeline that feeds RF tracks into our on-node sensor fusion engine. You will take this from bench prototype to field-deployed hardware on real customer sites within your first year.

What You Will Do

Design and build the RF sensing subsystem for our distributed detection nodes, from antenna selection through SDR integration to real-time signal processing software
Develop detection and classification for drone control and video links, including common commercial protocols, Wi-Fi based links, and custom or nonstandard emitters
Build robust performance in dense RF environments: urban clutter, industrial sites, and event settings where thousands of benign emitters compete with the signal you care about
Optimize for edge deployment: real-time processing on embedded compute, low power budgets, and operation without cloud connectivity
Work with our vendor partners on SDR hardware selection and integration
Take your subsystem into the field: bench testing, outdoor range testing, cold-weather characterization, and installation on customer sites
Collaborate closely with the founding team on sensor fusion, helping define how RF tracks combine with acoustic and visual detections
Help shape the engineering culture, tooling, and hiring of a team that will grow around you

What We Are Looking For

5+ years of hands-on RF or wireless systems engineering, or equivalent depth from research, defense, or serious personal work
Strong software-defined radio experience: GNU Radio, custom DSP pipelines, or equivalent frameworks on platforms such as USRP, Per Vices, or similar
Solid digital signal processing fundamentals: detection theory, filtering, spectral analysis, and working in low SNR conditions
Proficiency in C++ and Python for real-time signal processing
Experience with at least one of: drone RF protocols, wireless protocol reverse engineering, spectrum monitoring, electronic warfare, or radar
Comfort with hardware: you can work with antennas, front ends, and test equipment, and you are willing to stand in a field in February to prove your system works
Eligibility to work in Canada and ability to obtain Canadian security clearance and Controlled Goods Program registration

Nice to have

Experience with embedded Linux and edge compute platforms (NVIDIA Jetson or similar)
Direction finding, TDOA, or multi-sensor geolocation experience
Background in counter-UAS, EW, SIGINT, or spectrum sensing
Familiarity with FPV drone ecosystems and their radio links (ExpressLRS, analog video, digital video links)
Machine learning applied to RF signal classification
Prior experience at an early-stage startup or on a small team shipping hardware

Why this role

Foundational ownership. You are hire number one. The RF layer is the front door of the whole system, and it will be yours.
Real deployments, fast. Our first paid customer deployments are targeted within months, not years. Your work goes onto real sites quickly.
A problem that matters. Drone threats to infrastructure, events, and defense are growing faster than anyone can field answers. Canada is funding sovereign solutions right now, and we are positioned for that window.
Hard technical conditions by design. If you want your work stress-tested by minus 40 temperatures, contested spectrum, and no cloud to lean on, this is the job.
Equity and early-stage upside. Meaningful founding-team equity, competitive salary, and a seat at the table as the company scales.

Compensation And Logistics

Competitive salary plus meaningful early-stage equity
Based in Edmonton, Alberta or Toronto, Ontario – on-site (this is a hardware role; the lab is where the work is)

Relocation support available for the right candidate

First Name*

Last Name*

Email Address*

Country*

Linkedin*

Position*

Salary Expectation*

Describe an SDR project you've built end-to-end (e.g., with GNU Radio, USRP, Per Vices, or similar). What was the signal chain, and what problem were you solving?

Tell us about a signal detection or classification problem you solved in a low-SNR or RF-dense environment. What approach did you take and how did you validate it worked?

What's an example of real-time signal processing code you've shipped in C++ or Python? What were the latency/throughput constraints?

Which of these do you have direct experience with - drone RF protocols, wireless protocol reverse engineering, spectrum monitoring, electronic warfare, or radar? Describe the specific work.

Are you currently eligible to work in Canada, and are you able to obtain Canadian government security clearance and Controlled Goods Program registration?

This role is on-site in Edmonton or Toronto and involves outdoor field testing, including in winter. Confirm you're able to work on-site and willing to do outdoor field work in cold conditions.

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More about this job

Responsibilities

Design and deliver the RF sensing subsystem end to end, including antenna selection, SDR integration, real-time signal detection and classification, and integration of RF tracks with the sensor fusion engine. Validate and optimize the system for low-power edge deployment in challenging RF and weather conditions, from bench testing through field deployment at customer sites.

Requirements

Candidates need at least five years of hands-on RF or wireless systems engineering experience, strong SDR and DSP expertise, and proficiency in C++ and Python for real-time signal processing. They must have relevant experience in areas such as drone RF protocols, protocol reverse engineering, spectrum monitoring, electronic warfare, or radar, be eligible to work in Canada, and be able to obtain Canadian security clearance and Controlled Goods Program registration.

Skills

Radio Frequency Engineering
Software-Defined Radio
Digital Signal Processing
C++
Python
Signal Detection
Signal Classification
Wireless Protocol Reverse Engineering
GNU Radio
Embedded Linux
Real-Time Processing
Spectrum Monitoring
Antenna Integration
Sensor Fusion
Electronic Warfare
Counter-UAS

Benefits

Equity

Visa sponsorship

Not detected in the job text

Keywords

RF Sensing
Software-Defined Radio
GNU Radio
USRP
Per Vices
Digital Signal Processing
Detection Theory
Filtering
Spectral Analysis
Low-SNR Detection
Drone Control Links
Drone Video Links
Wi-Fi
Wireless Protocol Reverse Engineering
Spectrum Monitoring
Electronic Warfare
Radar
C++
Python
Embedded Linux
NVIDIA Jetson
Direction Finding
TDOA
Sensor Fusion
Edge Computing
FPV Drones
ExpressLRS
Machine Learning
Canadian Security Clearance
Controlled Goods Program

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