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Cuda Kernel Engineer information

What are some common challenges faced by Cuda Kernel Engineers when optimizing GPU code for performance?

Cuda Kernel Engineers often encounter challenges such as managing memory hierarchy efficiently, minimizing data transfer between host and device, and avoiding thread divergence. Ensuring optimal occupancy and maximizing parallelism while preventing bottlenecks like bank conflicts or uncoalesced memory access are also key concerns. Collaborating closely with software architects and data scientists is common, as solutions frequently require balancing algorithmic accuracy with hardware limitations. Addressing these challenges requires continuous profiling, testing, and iterative optimization.

What are Cuda Kernel Engineers?

Cuda Kernel Engineers are specialized software developers who design, implement, and optimize parallel computing algorithms using NVIDIA's CUDA platform. They write 'kernels,' which are functions that run on Graphics Processing Units (GPUs) to accelerate computational tasks in areas such as machine learning, scientific simulations, and graphics rendering. These engineers need strong skills in C/C++ programming, GPU architecture, and performance optimization techniques. Their work is crucial for applications that require high-speed data processing and efficient resource utilization.

What are the key skills and qualifications needed to thrive as a CUDA Kernel Engineer, and why are they important?

To thrive as a CUDA Kernel Engineer, you need strong proficiency in C/C++ programming, parallel computing concepts, and a solid foundation in GPU architectures, typically supported by a degree in computer science or a related field. Expertise in NVIDIA CUDA toolkits, GPU profiling tools like Nsight, and familiarity with version control systems are essential. Analytical thinking, problem-solving abilities, and effective collaboration skills help engineers optimize code and work well within development teams. These skills and qualities are crucial for delivering high-performance, scalable GPU solutions in computationally intensive applications.
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Cuda Kernel Engineer jobs near you

Senior CUDA C++ Software Engineer

Grey Matters Defense Solutions, LLC

Arlington, VA • On-site

$141K - $186K/yr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Job Summary:
Grey Matters Defense Solutions, LLC is a specialized firm in software development and data analytics for the defense and intelligence sectors. The Senior CUDA/C++ Software Engineer role involves designing, developing, and optimizing high-performance GPU-accelerated software solutions for advanced signal processing and RF exploitation.
Responsibilities:
• Design, develop, and maintain GPU-accelerated applications using CUDA and modern C++.
• Develop custom CUDA kernels optimized for performance, scalability, and maintainability.
• Implement efficient memory management strategies utilizing shared memory, pinned memory, unified memory, and asynchronous transfers.
• Optimize GPU utilization through concurrency, streams, kernel fusion, and multi-GPU processing techniques.
• Integrate GPU-accelerated capabilities into larger software systems and mission applications.
• Analyze and optimize application performance across CPU and GPU architectures.
• Profile applications using NVIDIA Nsight and related performance analysis tools.
• Identify and resolve bottlenecks related to memory bandwidth, kernel execution, synchronization, and data movement.
• Develop benchmark frameworks and performance regression testing capabilities.
• Develop clean, maintainable, and well-documented code using modern C++ standards.
• Participate in software architecture, design reviews, and code reviews.
• Build automated unit, integration, and performance testing frameworks.
• Support CI/CD pipelines and automated build environments.
• Collaborate with cross-functional engineering teams to deliver mission-critical software capabilities.
Qualifications:
Required:
• 8+ years of professional software engineering experience.
• 5+ years of experience developing high-performance applications in C++.
• 3+ years of hands-on CUDA development experience in production environments.
• Experience optimizing applications for throughput, latency, memory utilization, and scalability.
• Experience developing software on Linux platforms.
• Bachelor's degree or higher in Computer Science, Computer Engineering, Electrical Engineering, Applied Mathematics, Physics, or a related STEM discipline.
• C++17/20
• CUDA
• Python
• Linux Development
• Git
• CUDA Kernel Development
• NVIDIA GPU Architecture
• CUDA Streams and Concurrency
• Memory Optimization
• Multi-GPU Processing
• Nsight Profiling
• cuFFT
• cuBLAS
• Object-Oriented Design
• Design Patterns
• Unit Testing
• CI/CD
• Performance Benchmarking
• Software Architecture
• Digital Signal Processing
• RF Systems
• IQ Data Processing
• SIGINT Applications
• High-Performance Computing
Preferred:
• Experience with DSP, RF signal processing, and SIGINT applications.
Company:
Grey Matters Defense Solutions, LLC is a specialized enterprise dedicated to software development and tailored big data analytics, catering to the unique needs of the intelligence community, Department of Defense, and key national agencies. Founded in 2016, the company is headquartered in Denver, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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