Senior GPU Raytracing Engineer

Job not on LinkedIn

🕒 April 22

🏄 California – Remote

🏄 California – Remote

💵 $184k - $287.5k / year

⏰ Full Time

🟠 Senior

👷🏻‍♀️ Engineer

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👻 Ghost score 46%

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NVIDIA

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1993

🏥 Healthcare

🏭 Manufacturing

🤖 Artificial Intelligence

Healthcare • Manufacturing • Artificial Intelligence

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• Architect and implement a GPU ray-tracing engine for real-time, GPU-accelerated radio-signal propagation in realistic 3-D environments • Produce volumetric radio maps including coverage, SINR, and best-server maps at multiple resolutions • Compose radio maps across cells, frequencies, and beam configurations • Deliver per-link multipath channel updates at millisecond cadence for production RAN stacks • Develop adaptive algorithms that exploit temporal coherence • Design algorithms, data structures, and multi-GPU scaling strategies for sub-millisecond propagation updates • Contribute foundational technology for 5G and 6G network simulation using NVIDIA GPU and ray-tracing platforms

🎯 Requirements

• 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) • Track record of writing production-quality GPU code • Proficiency in GPU-friendly spatial data structures (BVH, space-filling curves, hash maps) • 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) • Ability to implement and validate a propagation engine • Impactful publications in GPU ray tracing, real-time rendering, or deterministic propagation modelling

🏖️ Benefits

• Equity • Benefits

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