Distributed Machine Learning Engineer
Team: Engineering
Location: Sunnyvale, CA
Commitment: Full-time
Workplace Type: onsite
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
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