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Principal RF Engineer

Spire Law - Cambridge, Ontario, Canada

Posted Jun 10, 2026

Benefits

Parental leave
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Non-birth-parent leave
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Family-building benefits
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  • Adoption assistance: Not verified
  • Surrogacy assistance: Not verified
Mental health support
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Relocation assistance
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Childcare support
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Learning budget
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Verification
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Salary
$152K-$180K not verified - source not recorded; timestamp not recorded

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Market context

U.S. role benchmark (BLS OEWS)
$111,944 U.S. median for this role
Projected growth (BLS Employment Projections)
+13.7% - Much faster than average

U.S. benchmark only; posted salary is not compared across countries or currencies.

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

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Weekend work
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Application

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Assessment
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Deadline
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Where they hire

State eligibility is not yet verified.

About this role

Principal RF Engineer Cambridge, Ontario, Canada Principal RF Engineer You will own the mathematical and physical foundations of one of the few operational commercial space-based RF geolocation systems in active customer use today. The core problem: estimating the position of RF emitters using time difference of arrival (TDOA), frequency difference of arrival (FDOA), and angle of arrival (AoA) measurements collected by a constellation of low Earth orbit (LEO) satellites. You will formulate estimation problems, develop and validate algorithms, characterize error sources, and drive performance improvements across all three measurement domains. You will inherit a working production geolocation system. This is not a greenfield research project. The algorithms exist, they run, and they produce results for real customers. Your job is to understand the existing system deeply, identify where performance is limited, and systematically improve it. Over time you will also extend the system with new measurement types and capabilities as mission requirements evolve. This is a hands-on, iterative role operating on real-world data with all its imperfections. Calibration is incomplete. Truth data is sparse. Operational constraints require pragmatic engineering tradeoffs. You will spend significant time examining real geolocation outputs, diagnosing performance issues, refining algorithms based on what the data shows, and shipping incremental improvements. The work cycle is not "design an algorithm and hand it off." It is: analyze outputs, identify the limiting error source, develop or refine an algorithmic solution, validate it against data, and repeat. You will work alongside software engineers who handle production implementation and infrastructure; your

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