Vaga de Research Research Software Engineer for AI Accelerator’s Software Stack Professional Multiple Cities
1 vaga: | Publicada em 21/04
- A Combinar
Sobre a vaga
IBMResearch Scientists are charting the future of Artificial
Intelligence,creatingbreakthroughs inquantum computing,discoveringhow blockchain
will reshape the enterprise, and much more. Join a team that is dedicated to
applying science tosome of today's most complex challenges, whether its
discovering a new way for doctors to help patients, teaming with environmentalists
to clean up our waterways or enabling retailers to personalize customer service.
Your Role and Responsibilities
As a Research Software Engineer at IBM Research, you will play a pivotal role in
driving the development, testing, and implementation of cutting-edge AI and Cloud
technologies. In this specific position, your responsibilities will span across
various aspects of software engineering, including design, construction, and
evaluation of software technologies, such as compilers, runtime components,
quantization algorithms, and supporting tools, to enable the use of AI
accelerators. In this role, you will have the opportunity to work on exciting
research initiatives, assess the potential applications of emerging AI and Cloud
technologies, and showcase the value of these technologies to both IBM's
businesses and strategic partners. You will be part of a diverse and inclusive
team of researchers and engineers, working together to push the boundaries of
Cloud-based AI platforms.
**Todas as nossas vagas são elegíveis para pessoas com deficiência ou
reabilitadas.** Required Technical and Professional Expertise
Strong programming skills in commonly used system programming languages, such as
C, C++, and Rust.
Demonstrated experience in developing and testing system software, such as
compilers, runtimes, quantization algorithms, debuggers, profilers, performance
analysis tools, etc.
Strong communication skills.
Fluent level of English
Preferred Technical and Professional Expertise
Demonstrated experience with GPU and TPU architectures.
Demonstrated experience with LLVM, CUDA and Triton compilers.
Demonstrated experience with GPTQ/AWQ quantizers.
Demonstrated experience with development of PyTorch hardware backends.