AI summary
The Senior GPU Raytracing Engineer will design and implement a real-time, GPU-accelerated propagation engine for predicting radio signal propagation in 3D environments, focusing on 5G and 6G network simulations.
Job Description
We are seeking a self‑motivated senior engineer for the Aerial Omniverse Digital Twin team. This hire will lead the design and implementation of a real‑time, GPU‑accelerated propagation engine that predicts how radio signals travel through realistic 3‑D environments — producing both per‑link channel characterisations and radio maps at the speed required by production RAN stacks! This position offers the opportunity to work on foundational technology for 5G and 6G network simulation, using NVIDIA's world‑class GPU and ray‑tracing platforms.
What you'll be doing:
As a member of NVIDIA's Aerial team, you will architect and implement a GPU ray‑tracing engine that operates at two time scales. At the planning scale, the engine produces volumetric radio maps — coverage, SINR, and best‑server maps at multiple resolutions, composable across cells, frequencies, and beam configurations — that network operators use to design and optimise deployments. At the real‑time scale, the same engine delivers per‑link multipath channel updates at the millisecond cadence that a production RAN stack requires, using adaptive algorithms that exploit temporal coherence to avoid recomputing what hasn't changed. Laying the foundations for real‑time ray tracing on GPU hardware — algorithms, data structures, and multi‑GPU scaling strategies that make sub‑millisecond propagation updates feasible — is the defining technical challenge of this role.
What we need to see:
- PhD in computer graphics, high‑performance computing, computational electromagnetics, or a closely related field (or equivalent experience).
8+ years of relevant experience.
- Hands‑on proficiency with CUDA and at least one GPU ray‑tracing framework (OptiX, Vulkan RT, Embree), with a track record of writing production‑quality GPU code.
- Proficiency in GPU‑friendly spatial data structures (BVH, space‑filling curves, hash maps) and the ability to reason about memory hierarchy, occupancy, and compute‑vs‑bandwidth trade‑offs at the kernel level.
- Working knowledge of electromagnetic wave propagation phenomena (reflection, transmission, diffraction, scattering) sufficient to implement and validate a propagation engine.
- Impactful publications in GPU ray tracing, real‑time rendering, or deterministic propagation modelling.
Ways to stand out from the crowd:
- Experience with real‑time or near‑real‑time ray‑tracing engines shipping in production systems.
- Prior work on multi‑GPU partitioning for ray‑tracing or large‑scale simulation workloads.
- Familiarity with 3GPP channel models and wireless network planning tools.
- Knowledge of geospatial coordinate systems and tiling schemes.
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Originally posted on Himalayas
About the job
- Posted on
- Sep 29, 2026
- Job type
- Full-time
- Location
- Canada, United StatesOn-site
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