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About the Institute of Foundation Models
We are a dedicated research lab for building, understanding, using,
and risk-managing foundation models. Our mandate is to advance
research, nurture the next generation of AI builders, and drive
transformative contributions to a knowledge-driven economy.
As part of our team, you’ll have the opportunity to work on the
Core of cutting-edge foundation model training, alongside
world-class researchers, data scientists, and engineers, tackling
the most fundamental and impactful challenges in AI development.
You will participate in the development of groundbreaking AI
solutions that have the potential to reshape entire industries.
Instrumental in establishing MBZUAI as a global hub for
high-performance computing in deep learning, driving impactful
discoveries that inspire the next generation of AI pioneers.
The Role
IFM is building the foundational compute infrastructure that will
power tomorrow’s breakthroughs in AI and computational science.
We’re looking for a High Performance Computing Software
Engineer to help us design, develop, and operate the software
systems that run our large-scale AI workloads.
In this role, you’ll work at the intersection of high-performance
computing and machine learning. You’ll be part of a team
responsible for crafting the software stack that enables training
of cutting-edge ML models—spanning 1000+ GPUs—and ensuring our
infrastructure is robust, performant, and developer-friendly.
Job Responsibilities
- Design and implement high-performance, distributed software
solutions for large-scale AI/ML training.
- Optimize low-level system components including Linux kernel,
GPU/accelerator kernels, and interconnects.
- Develop and tune communication libraries such as NCCL, MPI,
UCX, RCCL, and RDMA-based systems.
- Partner with ML researchers and engineers to support frameworks
like PyTorch, MegatronLM, and DeepSpeed in large-scale production
environments.
- Contribute to our scheduling, orchestration, and job management
systems, including Slurm and Kubernetes.
- Debug and resolve complex issues across the stack—from kernel
to container to model.
- Work closely with hardware vendors, upstream open-source
Communities, and internal teams to drive performance and
reliability improvements.
Skills & Experience
- Proven experience developing and optimizing software for
large-scale ML workloads (1000+ GPUs preferred).
- Deep understanding of Linux kernel internals and accelerator
(GPU) kernel development.
- Proficiency with distributed communication libraries (e.g.,
NCCL, RCCL, MPI, UCX, SHARP, Libfabric).
- Experience with ML frameworks like PyTorch, TensorFlow, JAX, or
MegatronLM.
- Strong knowledge of HPC job scheduling and orchestration tools
(e.g., Slurm, Kubernetes, Pyxis).
- Excellent debugging and systems performance tuning skills.
- A collaborative mindset with a focus on shared success and
technical excellence.
We may use artificial intelligence (AI) tools to support parts of
the hiring process, such as reviewing applications, analyzing
Resumes, or assessing responses and identifying potential
inconsistencies or verification signals in application materials
based on available information. These tools assist our recruitment
team but do not replace human judgment. Final hiring decisions are
ultimately made by humans. If you would like more information about
how your data is processed, please contact us.
About the Institute of Foundation Models
We are a dedicated research lab for building, understanding, using,
and risk-managing foundation models. Our mandate is to advance
research, nurture the next generation of AI builders, and drive
transformative contributions to a knowledge-driven economy.
As part of our team, you’ll have the opportunity to work on the
Core of cutting-edge foundation model training, alongside
world-class researchers, data scientists, and engineers, tackling
the most fundamental and impactful challenges in AI development.
You will participate in the development of groundbreaking AI
solutions that have the potential to reshape entire industries.
Instrumental in establishing MBZUAI as a global hub for
high-performance computing in deep learning, driving impactful
discoveries that inspire the next generation of AI pioneers.
The Role
IFM is building the foundational compute infrastructure that will
power tomorrow’s breakthroughs in AI and computational science.
We’re looking for a High Performance Computing Software
Engineer to help us design, develop, and operate the software
systems that run our large-scale AI workloads.
In this role, you’ll work at the intersection of high-performance
computing and machine learning. You’ll be part of a team
responsible for crafting the software stack that enables training
of cutting-edge ML models—spanning 1000+ GPUs—and ensuring our
infrastructure is robust, performant, and developer-friendly.
Job Responsibilities
- Design and implement high-performance, distributed software
solutions for large-scale AI/ML training.
- Optimize low-level system components including Linux kernel,
GPU/accelerator kernels, and interconnects.
- Develop and tune communication libraries such as NCCL, MPI,
UCX, RCCL, and RDMA-based systems.
- Partner with ML researchers and engineers to support frameworks
like PyTorch, MegatronLM, and DeepSpeed in large-scale production
environments.
- Contribute to our scheduling, orchestration, and job management
systems, including Slurm and Kubernetes.
- Debug and resolve complex issues across the stack—from kernel
to container to model.
- Work closely with hardware vendors, upstream open-source
Communities, and internal teams to drive performance and
reliability improvements.
Skills & Experience
- Proven experience developing and optimizing software for
large-scale ML workloads (1000+ GPUs preferred).
- Deep understanding of Linux kernel internals and accelerator
(GPU) kernel development.
- Proficiency with distributed communication libraries (e.g.,
NCCL, RCCL, MPI, UCX, SHARP, Libfabric).
- Experience with ML frameworks like PyTorch, TensorFlow, JAX, or
MegatronLM.
- Strong knowledge of HPC job scheduling and orchestration tools
(e.g., Slurm, Kubernetes, Pyxis).
- Excellent debugging and systems performance tuning skills.
- A collaborative mindset with a focus on shared success and
technical excellence.
We may use artificial intelligence (AI) tools to support parts of
the hiring process, such as reviewing applications, analyzing
Resumes, or assessing responses and identifying potential
inconsistencies or verification signals in application materials
based on available information. These tools assist our recruitment
team but do not replace human judgment. Final hiring decisions are
ultimately made by humans. If you would like more information about
how your data is processed, please contact us.
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