Description

Develop and maintain GPU-accelerated applications using CUDA.

Responsibilities

• Develop and maintain code for GPU-accelerated applications using CUDA.
• Identify and resolve performance issues and bugs related to CUDA implementations.
• Analyze and optimize algorithm performance through parallelization and memory usage optimizations.
• Collaborate with cross-functional teams to integrate CUDA optimizations into existing software architecture.
• Stay updated with latest trends and best practices in CUDA and parallel computing.

Required Skills

• Minimum 5 years of software development experience.
• At least 2 years of specific experience in CUDA.
• Proficiency in C/C++ programming languages.
• Expertise in CUDA Performance Optimization and best practices.
• Experience with CUDA version 12.0 or above, preferably 12.3.
• Familiarity with cuBLAS, cuDNN, and Thrust libraries.
• Strong understanding of GPU architectures and resource management.
• Knowledge of parallel computing patterns, memory management, and multi-threading.
• Experience with Large Language Models (LLMs) and their deployment on GPU infrastructure.

Preferred Skills

• Bachelor's degree in Computer Science, Computer Engineering, or related fields.

Key Skills

Education

Bachelor's Degree