GPU Software Engineer
Hire FeedAbout the role
Role: GPU Software Engineer (Remote)
Location: Remote (Work from Anywhere)
Job Type: Contract
Payout: $60 - $85/hour
Role Overview:
We are hiring for one of our clients, seeking a GPU Programming Software Engineer to work on a contract basis. The role involves developing high-performance computing solutions leveraging GPU architectures for computational workloads. You will optimize parallel processing frameworks and implement GPU-accelerated algorithms for large-scale data processing.
Key Responsibilities:
- Design and implement GPU-optimized software solutions for high-performance computing applications
- Develop and maintain CUDA/OpenCL-based kernels and libraries for parallel computation
- Profile and optimize existing codebases to improve GPU utilization and reduce latency
- Collaborate with cross-functional teams to integrate GPU acceleration into existing workflows
- Write unit tests and benchmarks to validate performance improvements and correctness
Required Skills & Qualifications:
- Proficiency in CUDA programming and GPU architecture optimization
- Experience with OpenCL, HIP, or other GPU computing frameworks
- Strong C/C++ programming skills with a focus on performance tuning
- Familiarity with parallel algorithms and data structures
- Knowledge of numerical computing libraries like cuBLAS, cuFFT, or Thrust
More About the Opportunity:
This role offers a unique opportunity to work with a global leader in the Technology, Information and Internet industry, contributing to the development of scalable GPU solutions for industry-specific computational challenges. The position requires independent problem-solving and the ability to deliver high-performance code in a fast-paced environment.
Equal Opportunity Employer:
We hire based on skills and expertise. All qualified candidates are welcome regardless of background, experience, or prior employment history. Applications are reviewed solely on demonstrated technical ability and qualifications.
Apply Now!
Responsibilities
- Design and implement GPU-optimized software solutions for high-performance computing applications
- Develop and maintain CUDA/OpenCL-based kernels and libraries for parallel computation
- Profile and optimize existing codebases to improve GPU utilization and reduce latency
- Collaborate with cross-functional teams to integrate GPU acceleration into existing workflows
- Write unit tests and benchmarks to validate performance improvements and correctness
Qualifications
- Proficiency in CUDA programming and GPU architecture optimization
- Experience with OpenCL, HIP, or other GPU computing frameworks
- Strong C/C++ programming skills with a focus on performance tuning
- Familiarity with parallel algorithms and data structures
- Knowledge of numerical computing libraries like cuBLAS, cuFFT, or Thrust
Skills mentioned
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