$92K - $121K/yr
... programming, and the challenge of converting algorithmic concepts into production-ready software ... Develop and maintain software in CUDA C/C++ for NVIDIA GPU-based systems. Translate and optimize ...
New
$92K - $121K/yr
... programming, and the challenge of converting algorithmic concepts into production-ready software ... Develop and maintain software in CUDA C/C++ for NVIDIA GPU-based systems. Translate and optimize ...
New
Tulsa, OK · On-site
$111K - $147K/yr
... programming, and the challenge of converting algorithmic concepts into production-ready software ... Develop and maintain software in CUDA C/C++ for NVIDIA GPU-based systems. Translate and optimize ...
New
Tulsa, OK · On-site
$111K - $147K/yr
... programming, and the challenge of converting algorithmic concepts into production-ready software ... Develop and maintain software in CUDA C/C++ for NVIDIA GPU-based systems. Translate and optimize ...
New
$91K - $119K/yr
Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we ... CUDA,NCCL, drivers, and relevant libraries * Familiarity with containerized environments (e.g ...
$91K - $119K/yr
Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we ... CUDA,NCCL, drivers, and relevant libraries * Familiarity with containerized environments (e.g ...
Familiarity with parallel programming models (MPI, OpenMP) and scientific computing frameworks ... Understanding of GPU computing and accelerator technologies (CUDA, OpenACC). * Experience ...
Familiarity with parallel programming models (MPI, OpenMP) and scientific computing frameworks ... Understanding of GPU computing and accelerator technologies (CUDA, OpenACC). * Experience ...
Familiarity with parallel programming models (MPI, OpenMP) and scientific computing frameworks ... Understanding of GPU computing and accelerator technologies (CUDA, OpenACC). * Experience ...
Familiarity with parallel programming models (MPI, OpenMP) and scientific computing frameworks ... Understanding of GPU computing and accelerator technologies (CUDA, OpenACC). * Experience ...
$25.75 - $30.29
5% of jobs
$30.29 - $34.83
10% of jobs
$34.83 - $39.37
9% of jobs
$40.34 is the 25th percentile. Wages below this are outliers.
$39.37 - $43.91
7% of jobs
$43.91 - $48.45
15% of jobs
The median wage is $49.84 / hr.
$48.45 - $52.99
14% of jobs
$57.10 is the 75th percentile. Wages above this are outliers.
$52.99 - $57.53
17% of jobs
$57.53 - $62.07
14% of jobs
$62.07 - $66.61
6% of jobs
$66.61 - $71.15
3% of jobs
$71.15 - $75.69
0% of jobs
$25
$50
$75
| Aspect | Cuda Programming | GPU Developer |
|---|---|---|
| Required Credentials | Knowledge of CUDA, C/C++, parallel computing | Knowledge of GPU architecture, CUDA, OpenCL, C/C++ |
| Work Environment | High-performance computing, scientific research, AI | Graphics, gaming, scientific visualization, AI |
| Industry Usage | Tech companies, research labs, AI firms | Gaming, entertainment, tech, research |
While Cuda Programming focuses specifically on writing code using NVIDIA's CUDA platform for parallel processing, GPU Developers have a broader role that includes designing, optimizing, and implementing GPU-based solutions across various platforms and technologies. Both roles require knowledge of GPU architecture and programming languages like C/C++, but GPU Developers often work on a wider range of applications beyond CUDA-specific projects.
$92K - $121K/yr
Full-time
Posted yesterday
New
Job Title: Real-time Development Engineer 4
Job Code : 41937
Job Location: Tulsa, OK
Schedule: 9/80 employees work 9 out of 14 days- totaling 80 hours worked- and have every other Friday off
Job Description:
L3Harris is seeking a Developer, Software Engineering with experience in CUDA, C/C++, and Python to support the development of high-performance GPU-accelerated software for advanced mission applications. The selected candidate will work closely with software and algorithm teams to translate computational and image-processing algorithms into efficient CUDA C/C++ implementations for execution on NVIDIA GPU platforms.
This role is ideal for an engineer who enjoys performance optimization, parallel programming, and the challenge of converting algorithmic concepts into production-ready software. The position includes design, implementation, integration, profiling, test, and optimization of GPU-based software in a Linux development environment. Our development efforts aim to achieve the best possible performance to meet demanding real-time requirements.
Essential Functions:
Develop and maintain software in CUDA C/C++ for NVIDIA GPU-based systems.
Translate and optimize computational algorithms into efficient GPU implementations.
Support development of image processing and related high-performance software applications.
Analyze existing software and algorithms to identify opportunities for parallelization and acceleration.
Improve software performance through optimization of kernel execution, memory usage, and data movement.
Develop and execute unit, integration, and performance tests to validate functionality and accuracy.
Collaborate with cross-functional teams including software, systems, and algorithm engineers.
Participate in software design reviews, code reviews, and technical discussions.
Support software integration and debugging in Linux-based environments.
Document software design, implementation, test results, and performance findings.
Qualifications:
Bachelor's Degree and a minimum of 6 years of prior relevant software experience. Graduate Degree and a minimum of 4 years of prior related experience. In lieu of a degree, minimum of 10 years of prior related experience.
Minimum 6 years of experience with C/C++.
Minimum 2 years of experience with Python.
Minimum 4 years of experience with NVIDIA CUDA.
Experience developing software in Linux environments.
Experience implementing or optimizing algorithms for performance-sensitive applications.
Experience using source control and standard software development practices.
Must be eligible to obtain a U.S. security clearance.
Preferred Additional Skills:
Experience with GPU profiling and performance analysis tools such as Nsight Systems, Nsight Compute, NVIDIA Visual Profiler, Compute Sanitizer.
Experience with image processing and/or computer vision applications.
Experience with TensorRT, cuFFT, cuBLAS, cuDNN, NPP, Thrust, and CUB.
Experience with Containerization with technologies such as Docker is a plus.
Experience using DevOps pipelines and tooling is a plus.
Experience translating prototype or research algorithms into production-quality implementations.
Familiarity with software testing, benchmarking, and debugging techniques in high-performance computing environments.
Experience developing for multiple CUDA Architectures and Compute Capabilities
Knowledge of GPU Direct/RDMA, NVIDIA containerization, machine parallelism
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