Senior GPU Raytracing Engineer

NVIDIA•Santa Clara, CA

6d•$184,000 - $356,500

About The Position

NVIDIA is seeking a self-motivated senior engineer for its Aerial Omniverse Digital Twin team. The engineer will lead the design and implementation of a real-time, GPU-accelerated propagation engine that predicts radio-signal travel through realistic 3-D environments, producing per-link channel characterisations and radio maps at speeds suitable for production RAN stacks. The role focuses on foundational technology for 5G and 6G network simulation using NVIDIA GPU and ray-tracing platforms. The engineer will architect and implement a GPU ray-tracing engine operating at two time scales. For planning, it will produce volumetric radio maps—including coverage, SINR, and best-server maps at multiple resolutions—that can be composed across cells, frequencies, and beam configurations for deployment design and optimisation. In real time, the engine will deliver per-link multipath channel updates at millisecond cadence, using adaptive algorithms and temporal coherence to avoid unnecessary recomputation. The defining technical challenge is establishing algorithms, data structures, and multi-GPU scaling strategies that make sub-millisecond propagation updates feasible. The position offers equity and benefits. The stated base salary ranges are $184,000–$287,500 for Level 4 and $224,000–$356,500 for Level 5, determined by location, experience, and other objective job-related factors. Applications will be accepted at least until November 6, 2026. This posting is for an existing vacancy.

Requirements

PhD in computer graphics, high-performance computing, computational electromagnetics, or a closely related field, or equivalent experience.
At least 8 years of relevant experience.
Hands-on proficiency with CUDA and at least one GPU ray-tracing framework: OptiX, Vulkan RT, or Embree.
Track record of writing production-quality GPU code.
Proficiency in GPU-friendly spatial data structures such as BVHs, space-filling curves, and hash maps.
Ability to reason about memory hierarchy, occupancy, and compute-versus-bandwidth trade-offs at the kernel level.
Working knowledge of electromagnetic wave-propagation phenomena—including reflection, transmission, diffraction, and scattering—sufficient to implement and validate a propagation engine.
Impactful publications in GPU ray tracing, real-time rendering, or deterministic propagation modelling.

Nice To Haves

Experience with real-time or near-real-time ray-tracing engines shipped 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.

Responsibilities

Lead the design and implementation of a real-time, GPU-accelerated radio-propagation engine.
Architect and implement GPU ray-tracing algorithms for volumetric radio maps used in network planning and optimisation.
Deliver real-time per-link multipath channel updates at millisecond cadence for production RAN stacks.
Develop adaptive algorithms that use temporal coherence to avoid recomputing unchanged propagation results.
Establish algorithms, data structures, and multi-GPU scaling strategies to enable sub-millisecond propagation updates.
Produce planning-scale maps including coverage, SINR, and best-server maps at multiple resolutions, composable across cells, frequencies, and beam configurations.