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Weekend Software Engineer Gpu Jobs in Oklahoma (NOW HIRING)

Senior Software Engineer Specialist

Tulsa, OK · On-site

$92K - $121K/yr

Real-time Development Engineer 4 Job Code : 41937 Job Location: Tulsa, OK Schedule: 9/80 employees ... Develop and maintain software in CUDA C/C++ for NVIDIA GPU-based systems. Translate and optimize ...

Software Engineer II

Tulsa, OK · On-site

$80 - $110/hr

Software Engineer II Full Time Tulsa, OK, US 6 days ago Requisition ID: 1362 Summary Design, code ... Travel is typically overnight and often includes weekends. This may include visits to customer ...

Software Engineer I - Tulsa Full Time Tulsa, OK, US 10 days ago Requisition ID: 1361 Summary Design ... Travel is typically overnight and often includes weekends. This may include visits to customer ...

Software Engineer II

Tulsa, OK · On-site

$85K - $117K/yr

... systems engineers to identify and evaluate interface requirements between software and hardware ... Travel is typically overnight and often includes weekends. This may include visits to customer ...

Software Engineer I - Tulsa Full Time Tulsa, OK, US 7 days ago Requisition ID: 1361 Summary Design ... Travel is typically overnight and often includes weekends. This may include visits to customer ...

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Weekend Software Engineer Gpu information

What is the difference between Weekend Software Engineer Gpu vs Weekend Software Engineer Cloud?

AspectWeekend Software Engineer GpuWeekend Software Engineer Cloud
Required CredentialsBachelor's in Computer Science or related, experience with GPU programmingBachelor's in Computer Science or related, experience with cloud platforms
Work EnvironmentOn-site or remote, focused on GPU hardware and softwareRemote or hybrid, focused on cloud infrastructure and services
Industry UsageGaming, AI, high-performance computingWeb services, SaaS, enterprise solutions
Search & Comparison IntentYesYes

The Weekend Software Engineer Gpu and Weekend Software Engineer Cloud roles share similar educational backgrounds and work environments but differ in focus areas. The GPU role emphasizes hardware acceleration and high-performance computing, while the Cloud role centers on cloud infrastructure and services. Both are in high demand and often compared by job seekers exploring flexible tech roles.

What are the most commonly searched types of Software Engineer Gpu jobs in Oklahoma?

The most popular types of Software Engineer Gpu jobs in Oklahoma are:

Senior Software Engineer Specialist

L3HHCM20

Tulsa, OK • On-site

$92K - $121K/yr

Full-time

Posted 29 days ago


Job description

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

 #LI-LT2