Distributed Machine Learning Engineer

SunnyvaleFull-timemid

Data ScienceMachine Learning EngineerDataData & AI

0 views0 saves0 applied

Apply Now

Quick Summary

Overview

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,

Technical Tools

Data ScienceMachine Learning EngineerDataData & AI

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.

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.

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