Aerospace systems engineering and testing for defense contractors
Aviya designs and tests mission-critical aerospace systems for major defense and engine manufacturers. The stack reveals a heavy simulation and embedded-systems focus (MATLAB, Simulink, LabVIEW, VHDL, TestStand) paired with modern cloud and data tools (Azure DevOps, Kafka, Power BI, AWS), indicating a shift toward real-time monitoring and ML-driven diagnostics. Active hiring is concentrated in mid-level engineering roles across three North American sites, with projects spanning engine programs, hardware test automation, and fault classification—suggesting capacity scaling in both certification pathways and operational analytics.
Aviya Aerospace Systems provides engineering services, embedded systems design, and test infrastructure for the world's largest aerospace and defense primes. The company specializes in gas turbine modeling, safety-critical electronics design, real-time embedded systems simulation, and advanced test bench technology. Headquartered in Mississauga, Ontario, with engineering centers in Montreal and East Hartford, the 201–500-person company serves large OEMs across engine development, hardware certification, and in-service performance monitoring. Work spans the full product lifecycle from design validation through production test and fleet diagnostics.
Engineering-focused: MATLAB, Simulink, LabVIEW, VHDL, C++, Python for modeling and embedded design; Azure DevOps and Subversion for version control; Kafka for data streaming; Power BI, SQL Server, PostgreSQL for analytics; DO-178C and ISO 26262 certification frameworks.
New engine programs and service enablement; hardware test panel development for aerospace certification; engine performance trend monitoring; machine learning fault classification; relational database data aggregation for in-service analytics.
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Aviya Aerospace Systems's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
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