Senior AI GPU Performance Engineer

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Written by AI from the job title and company, not by Modular, so some details may not match this job. The employer's own page has the real description.

Overview

The Senior AI GPU Performance Engineer at Modular will play a pivotal role in enhancing the performance of AI-driven applications through meticulous analysis and optimization of GPU architectures. This individual will be responsible for identifying performance bottlenecks, implementing performance tuning strategies, and collaborating with cross-functional teams to ensure that the GPU solutions meet the high standards expected from cutting-edge AI workflows. The role demands a deep understanding of GPU architectures, performance profiling tools, and an ability to translate technical findings into actionable improvements that align with Modular's mission of delivering high-efficiency solutions.

Job Responsibilities

• Analyze and optimize GPU performance for various AI applications, focusing on high throughput and low latency.
• Develop and implement performance benchmarking strategies to assess the efficiency of GPU architectures.
• Collaborate closely with hardware and software engineering teams to propose enhancements and optimizations.
• Utilize performance profiling tools to diagnose issues and deliver actionable recommendations for improvement.
• Design and execute experiments to validate performance enhancements and report findings to stakeholders.
• Stay abreast of advances in GPU technologies and AI application frameworks to incorporate cutting-edge techniques.

Qualifications

• Bachelor's degree in Computer Science, Electrical Engineering, or a related field; Master’s degree preferred.
• 5+ years of experience in GPU performance engineering or a related domain.
• Proficiency in performance analysis tools such as NVIDIA Nsight, CodeXL, or similar.
• Strong programming skills in CUDA, C/C++, and Python.
• Deep understanding of GPU architectures and parallel computing principles.
• Experience with AI frameworks like TensorFlow, PyTorch, or MXNet.

Technologies & Tools

The position will leverage advanced GPU programming platforms and performance analysis tools, including but not limited to NVIDIA CUDA, TensorRT, and profiling tools such as NVIDIA Nsight. Familiarity with AI frameworks like TensorFlow and PyTorch will also be paramount in executing the job responsibilities effectively. Additionally, the role may require usage of version control systems and integrated development environments (IDEs) relevant to AI and GPU programming.

Ideal Candidates

Ideal candidates for the Senior AI GPU Performance Engineer position at Modular will exhibit strong analytical abilities and a passion for optimization in high-performance computing environments. They will possess excellent communication skills to collaborate with diverse teams, a proactive approach to troubleshooting and problem-solving, and a commitment to continual professional growth. A robust understanding of emerging technologies, coupled with the ability to adapt to fast-paced changes in the AI landscape, will further enhance their fit within the organization.