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Research Engineer - Menlo, United States - Acceler8 Talent
Description
Research Engineer (GPU Kernels)
Check all associated application documentation thoroughly before clicking on the apply button at the bottom of this description.
Are you an experienced professional in high-performance computing? If so, we have an exciting opportunity for you Our team is seeking individuals who are passionate about advancing technology to join us in developing cutting-edge algorithms and GPU kernels. If you thrive on challenges and excel in optimizing performance, this role might be the perfect fit for you.
About the Company
We're a leading player in the tech industry, committed to innovation and pushing the boundaries of what's possible. While we may not be the biggest name out there, our dedication to excellence sets us apart. Our team comprises driven individuals who are determined to shape the future of computing technology.
About the Role
As a High-Performance Computing Engineer, you'll play a crucial role in designing and developing algorithms and GPU kernels for inference and training. You'll have the opportunity to explore new applications for LLMs, contributing to groundbreaking advancements in the field. If you have a passion for fine-tuning performance and thrive in a fast-paced environment, we want to hear from you.
What We Can Offer You
We understand the importance of a competitive compensation package. That's why we offer a competitive salary, along with equity and a comprehensive benefits package. Our benefits include medical, dental, vision, PTO, and a 401(k) plan, ensuring our employees are well taken care of.
Key Responsibilities
We value individuals with a Master's or higher degree in Computer Science or Software Engineering, or those with 3+ years of relevant experience. Experience with CUDA, HIP, DPC++, or SYCL is highly desirable, as is proficiency in C, C++, and Python programming.
If you have a background in Compiler Engineering, Kernel Engineering, or GPU Engineering, this role may be perfect for you. Additionally, experience with high-performance and parallel computing, as well as programming DSPs, FPGAs, or GPUs, will be advantageous. We also welcome candidates with experience in open-source contributions or early-stage startups.
