HPC/RDMA Engineer

As an HPC/RDMA Engineer at Tensorwave, your main responsibilities include designing and implementing innovative networking solutions that cater to high-performance AI workloads. You will lead initiatives to explore and integrate new network fabrics to enhance scalability and efficiency within our AI cloud services. Additionally, you will ensure network reliability and security while troubleshooting complex issues to maintain optimal service levels.

To qualify for the HPC/RDMA Engineer role at Tensorwave, you should possess a Bachelor’s degree in Computer Science, Information Technology, or a related field. Furthermore, a minimum of 5 years of relevant experience in network engineering, specifically supporting high-performance computing and AI applications, is essential. Knowledge of BGP, Ethernet protocols, and experience with AMD and NVIDIA GPU ecosystems are also crucial.

An HPC/RDMA Engineer at Tensorwave should have strong knowledge of networking technologies, particularly BGP, Ethernet protocols, and RoCEv2. Familiarity with network security practices and a keen interest in exploring new network fabrics and technologies, especially in the realm of AI and cloud computing, is also highly beneficial.

The HPC/RDMA Engineer role is vital for Tensorwave’s AI initiatives, as it focuses on developing and managing the networking infrastructure that supports our advanced AI cloud services. By enhancing the performance and scalability of our systems, you enable more effective execution of AI projects, thus driving innovation and efficiency across the organization.

At Tensorwave, the work environment for an HPC/RDMA Engineer is dynamic and collaborative. You will work alongside a dedicated IT team focused on solving complex challenges in AI computing. Our culture promotes innovation, offering real opportunities for growth and development, making it an exciting place to be for those with a passion for technology and teamwork.

When answering this question, focus on specific projects where you’ve had to design or manage networking solutions for high-performance computing. Highlight your technical skills, the technologies you utilized, and the impact of your work on performance efficiency.

Share your methods for professional development, such as following key industry publications, attending conferences, participating in networking forums, or taking relevant courses. This shows your commitment to keeping your skills sharp as an HPC/RDMA Engineer at Tensorwave.

Discuss structured methodologies you use to diagnose and resolve networking problems, like utilizing monitoring tools, performing logs analysis, and how you collaborate with team members for comprehensive solutions, reflecting your strong problem-solving abilities.

When answering, detail the various security practices you implement, such as firewalls, network segmentation, and encryption. Provide examples from previous projects where you successfully maintained network security in high-demand environments.

Provide details about your hands-on experience with BGP and Ethernet protocols, discussing specific configurations you've worked on. Illustrating practical applications of these technologies will demonstrate your technical expertise relevant to the HPC/RDMA Engineer role.

Discuss RDMA's benefits, such as reduced latency and increased throughput. Use examples from your past experience on how utilizing RDMA has positively impacted performance in AI or HPC environments.

Share specific examples where you explored and integrated new network fabrics into existing systems. Discuss the challenges you faced and the successful outcomes, demonstrating your innovative approach to networking.

Emphasize the importance of aligning networking strategies with the goals of AI projects. Provide examples of how you’ve successfully collaborated with developers to ensure that network infrastructure supports AI initiatives.

Discuss the impact of AMD and NVIDIA GPUs on network performance. Share insights on optimizing network configurations specifically tailored for environments reliant on powerful GPU assets.

Share your perspective on emerging trends and innovations in networking as they relate to AI cloud services. Highlight your adaptability and eagerness to embrace new technologies, aligning with Tensorwave's innovative ethos.