Distributed Machine Learning Engineer

Job description

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. Strategic and innovative problem-solving skills will be 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 The Distributed ML Engineer will play a role at the forefront of optimizing performance for the machine learning software stacks, especially at training and inference, and support the team to develop new and cutting-edge systems. The ideal candidate will have a strong background in parallel computing, and hands-on experience in system level coding, debug methodologies, and large-scale machine learning experience. ### Key Responsibilities - Understand, analyze, profile, optimize, and provide guidance to the team on deep learning workloads on state-of-the-art hardware and software platforms to improve their efficiency with different levels of optimization - Design and implement performance benchmarks and testing methodologies to evaluate application performance - Build tools to automate workload analysis, workload optimization, and other critical workflows - Triage system issues and identify bottleneck and inefficiencies by analyzing the sources of issues and the impact on hardware, network and propose solutions to enhance GPU utilization - Support the team to develop appropriate kernels and systems for new model architectures and algorithms - Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies. - Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency). - Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback. - Represent MBZUAI at industry conferences and events, showcasing the institution’s cutting-edge HPC and deep learning capabilities and establishing MBZUAI as a global leader in AI research and innovation. - Perform all other duties as reasonably directed by the line manager that are commensurate with these functional objectives. ### Academic Qualifications - Ph.D. in CS, EE or CSEE with 1+ years working experience, OR - Masters in CS, EE or CSEE or equivalent experience with 2+ year working experience