Rendering Systems Engineer - Simulation & Synthetic Data

What you'll do

• Modify Unreal Engine rendering systems and build cloud job orchestration for rendering independent worlds or cameras across GPUs.
• Optimize GPU and hardware throughput with parallelization, caching, and high-performance interconnect communication; profile and diagnose compute and I/O bottlenecks.
• Integrate the renderer with internal toolchains, simulation, and data pipelines, and collaborate with research teams to improve iteration and robustness.

What they ask for

• Deep experience with Unreal Engine rendering architecture and engine-source customization, including shader pipelines and GPU resource synchronization.
• Strong performance-engineering skills, including profiling, roofline analysis, latency/throughput optimization, and root-cause analysis.
• Advanced low-level GPU optimization skills in CUDA/Vulkan, including kernel tuning, memory hierarchy, and bandwidth efficiency.
• High proficiency in C++, CUDA, and Python; practical Vulkan implementation experience.

Nice to have

• 3-4+ years of engineering experience in AI research labs, machine learning enterprises, or robotics and autonomous vehicle organizations.
• Familiarity with NVLink/NCCL or collective communications, large-scale generative or foundation-model deployment, or profiling and observability toolchains for graphics/GPU workloads.

Pay

$250K – $325K USD base salary

Tools

Unreal Engine, CUDA, Vulkan, C++, Python, Rust, Nanite, Lumen

AI focus

The role builds rendering systems for synthetic data generation and simulation, supporting research and data pipelines for spatial AI.