Job Summary
A GPU Engineer designs, develops, and optimizes software and systems that run on Graphics Processing Units (GPUs). The role focuses on high‑performance computing, graphics rendering, or compute workloads such as AI/ML, computer vision, and scientific simulations, ensuring maximum performance, scalability, and efficiency.
Key Responsibilities
- Design, develop, and optimize GPU‑accelerated software solutions
- Write and maintain high‑performance code using CUDA, OpenCL, Vulkan, DirectX, or Metal
- Optimize memory usage, latency, and throughput on GPU architectures
- Develop and debug graphics pipelines, shaders, or compute kernels
- Profile GPU performance and resolve bottlenecks using diagnostic tools
- Collaborate with CPU, driver, and hardware teams to ensure efficient integration
- Support AI/ML workloads by accelerating neural networks and data pipelines
- Analyze and adapt algorithms for parallel processing
- Ensure code scalability across different GPU architectures
- Document designs, performance benchmarks, and optimization strategies
Required Qualifications
- Bachelor's in Computer Engineering, Electrical Engineering, Computer Science, or related field
- Strong programming skills in C/C++ and at least one GPU programming framework (CUDA, OpenCL, etc.)
- Deep understanding of parallel computing concepts
- Experience with GPU memory models, threads, and synchronization
- Familiarity with graphics APIs (OpenGL, Vulkan, DirectX) or compute APIs
- Experience debugging and profiling GPU applications
Preferred Qualifications
- Experience with AI/ML frameworks (TensorFlow, PyTorch, ONNX)
- Knowledge of computer graphics, ray tracing, or real‑time rendering
- Familiarity with driver-level or kernel-level GPU development
- Experience optimizing for embedded or mobile GPUs
- Understanding of hardware architecture (SMs, warps, caches, pipelines)
Tools & Technologies
- NVIDIA CUDA / Nsight
- AMD ROCm
- OpenCL / Vulkan / DirectX / Metal
- Python for experimentation and tooling
- Linux and Windows development environments
- Performance profiling and benchmarking tools
Soft Skills
- Strong problem-solving and analytical skills
- Ability to explain complex performance concepts clearly
- Collaboration across hardware, firmware, and software teams
- Attention to detail and performance trade‑offs
All qualified applicants will receive consideration for employment without regard to race, color, national origin, age, ancestry, religion, sex, sexual orientation, gender identity, gender expression, marital status, disability, medical condition, genetic information, pregnancy, or military or veteran status. We consider all qualified applicants, including those with criminal histories, in a manner consistent with state and local laws, including the California Fair Chance Act, City of Los Angeles' Fair Chance Initiative for Hiring Ordinance, and Los Angeles County Fair Chance Ordinance.