Systems Research Engineer, GPU Programming

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

Job Overview

The Systems Research Engineer with a focus on GPU Programming at Together AI will be principally responsible for developing and optimizing high-performance systems that utilize GPU architectures for advanced computing applications. This role demands a fusion of strong programming skills and an analytical mindset, as the engineer will collaborate with interdisciplinary teams to drive innovations in AI research and applications. The successful candidate will be instrumental in enhancing system performance, developing algorithms, and ensuring the effective deployment of GPU resources to support cutting-edge research projects.

Job Responsibilities

• Design, implement, and optimize GPU-based algorithms for high-performance computing applications.
• Collaborate with cross-functional teams to integrate GPU programming into existing systems for improved performance.
• Analyze and document the performance of system components and suggest improvements based on findings.
• Support the development of software tools and workflows that optimize GPU resource usage.
• Conduct thorough testing and validation of GPU implementations to ensure reliability and accuracy.
• Stay current with industry trends and advancements in GPU technologies to enhance system capabilities.
• Provide mentorship and technical guidance to junior engineers and researchers in GPU programming techniques.

Qualifications

• Bachelor’s or Master's degree in Computer Science, Computer Engineering, or a related field.
• Proven experience in GPU programming using frameworks such as CUDA or OpenCL.
• Strong proficiency in programming languages including C++, Python, or similar languages.
• In-depth knowledge of parallel computing concepts and architectures.
• Experience with performance analysis and system optimization techniques.
• Familiarity with machine learning concepts and frameworks (e.g., TensorFlow, PyTorch) is a plus.
• Excellent problem-solving skills and the ability to work collaboratively in a fast-paced environment.

Technologies & Tools

The Systems Research Engineer will employ various technologies and tools including GPU programming frameworks such as CUDA and OpenCL, performance analysis tools, modern programming languages like C++ and Python, as well as machine learning frameworks like TensorFlow and PyTorch. Familiarity with version control systems (e.g., Git) and development environments is also essential for efficient collaboration and software development.

Ideal Candidates

Ideal candidates for this position are those who possess a blend of technical expertise and innovative thinking, paired with the ability to collaborate effectively within multidisciplinary teams. They should demonstrate a strong passion for exploring new computational techniques and have a proactive approach to problem-solving. A commitment to continuous learning and staying abreast of advancements in GPU technology will also set the best candidates apart in their role, contributing to the dynamic environment at Together AI.