Senior Software Engineer, C++ and CUDA - RAPIDS

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Job Overview

As a Senior Software Engineer specializing in C++ and CUDA on the RAPIDS team at NVIDIA, you will be instrumental in developing high-performance software solutions that enable accelerated data analysis and machine learning workflows. This role demands a strong understanding of parallel computing, graphics processing, and algorithm optimization to create novel features and enhancements within the RAPIDS ecosystem. You will collaborate with a diverse team of engineers and researchers to drive the implementation and deployment of cutting-edge data science frameworks, ultimately contributing to the advancement of GPU-accelerated data science tools.

Job Responsibilities

• Design and implement software features using C++ and CUDA to enhance the RAPIDS data science framework.
• Collaborate with cross-functional teams to define project requirements and deliver high-quality software solutions.
• Optimize algorithms and software performance for scalability and efficiency on various GPU architectures.
• Conduct code reviews and provide mentorship to junior engineers, fostering a culture of collaboration and continuous improvement.
• Stay updated with the latest technologies and industry trends to ensure RAPIDS remains competitive and innovative.
• Document software architecture and design decisions to maintain clear technical reference for the team.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field.
• 5+ years of professional experience in software development with a strong emphasis on C++ and CUDA programming.
• Proven experience in high-performance computing and parallel computing concepts.
• Strong understanding of data structures, algorithms, and software design principles.
• Experience with machine learning concepts and working within data science frameworks.
• Excellent problem-solving skills and ability to work effectively in a collaborative environment.

Technologies & Tools

This position primarily utilizes C++, CUDA, and RAPIDS libraries for accelerated data processing. Familiarity with deep learning frameworks such as TensorFlow and PyTorch, alongside tools for version control (Git) and continuous integration/deployment (CI/CD), are also crucial for effective collaboration and project implementation.

Ideal Candidates

The ideal candidate for this position will not only possess strong technical expertise but also demonstrate a proactive mindset and a passion for problem-solving. Characteristics such as effective communication skills, adaptability to rapidly changing technologies, and a genuine interest in advancing data science capabilities will significantly contribute to the success of the candidate in this role. Team players who can work collaboratively and bring innovative ideas are particularly well-suited for our dynamic environment.