Water resource engineer - in - training supporting flood, river, stormwater, and watercourse projects at Onterris. Assisting modelling, design, field investigations, and regulatory work.
About the role
- GPU Performance Engineer optimizing neural reconstruction and Gaussian Splatting workloads at NVIDIA. Collaborating with global teams to enhance GPU performance in cutting-edge 3D systems.
Responsibilities
- Profile end-to-end neural reconstruction workflows and identify bottlenecks across data loading, initialization, training, rendering, evaluation, and export
- Improve CUDA and PyTorch performance for Gaussian Splatting and neural reconstruction workloads
- Analyze GPU performance using tools such as Nsight Systems, Nsight Compute, NVTX, PyTorch Profiler, CUDA events, and benchmark dashboards
- Optimize sparse and irregular rendering workloads
- Validate that performance improvements preserve reconstruction quality, numerical behavior, camera/lidar correctness, and production reliability
- Build repeatable benchmarks, regression tests, and profiling workflows to catch performance and quality regressions early
- Collaborate with researchers, CUDA engineers, ML engineers, and production teams to turn promising prototypes into maintainable, reviewable, production-quality code
Requirements
- BS, MS, PhD, or equivalent experience in Computer Science, Computer Engineering, Electrical Engineering, Applied Math, Robotics, Computer Vision, Machine Learning, or a related field
- 12+ years of experience
- Strong programming skills in Python and C++
- Hands-on experience with PyTorch or a similar tensor/autograd framework
- Experience optimizing GPU-accelerated workloads using CUDA, C++/CUDA extensions, or related GPU programming approaches
- Practical experience with profiling and performance analysis
- Ability to develop benchmarks and validate that optimizations preserve correctness, numerical behavior, and user-visible quality.
Benefits
- Highly competitive salaries
- Comprehensive benefits package
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