Software Engineer III - Edge Computing

Proven ability to lead engineering teams in a structured software product development environment

Four (4) year to seven (7) years of software engineering design experience

Proven experience leading software engineering teams through full development lifecycle

Proven experience with CUDA or similar parallel computing standards.

Ability to reason about heterogeneous memory architectures (Unified Memory, Zero-Copy).

Solid experience with Linux system administration, container orchestration (Kubernetes/Docker), and networking configuration.

$104,236-$163,300

Please click “Apply” to submit your application.

Voyager offers a comprehensive, total compensation package, which includes competitive salary, a discretionary annual bonus plan, paid time off (PTO), a comprehensive health benefit package, retirement savings, wellness program, and various other benefits. When you join our team, you’re not just an employee; you become part of a dynamic community dedicated to innovation and excellence.

To conform to U.S. Government export regulations, including the International Traffic in Arms Regulations (ITAR) (22 CFR Parts 120–130) and the Export Administration Regulations (EAR) (15 CFR Parts 730–774), applicants for this position must be a U.S. Person: a US Citizen, a lawful permanent resident of the U.S., or a protected individual as defined by 8 U.S.C. § 1324b(a)(3). Applicants must be eligible to obtain any required export authorizations from the U.S. Department of State or the U.S. Department of Commerce.

Able to obtain and maintain a U.S. security clearance

Voyager is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.

The Senior Edge Computing Engineer is a hands-on developer role responsible for the core performance of our fielded systems.

You will own critical subsystems, utilizing advanced GPGPU techniques to process high-velocity data streams in real-time.

You will work with minimal supervision to architect and implement solutions that run on diverse hardware targets, from multi-GPU rackmount servers to power-constrained embedded modules.

High-Performance Computing:

Design and implement high-throughput processing pipelines using Modern C++ and GPU-accelerated frameworks (e.g., CUDA, Holoscan, ROCm).

Write and optimize custom GPU kernels for signal processing operations, managing memory coalescing and host-to-device data transfers to minimize latency.