Machine Learning Engineer — GPU Kernel

Institute of Foundation Models
  • Sunnyvale, California
  • $150,000–$450,000 Per Year
  • Autofill and Review
14 days ago

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 GPU Kernel 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.

This role focuses on CUDA kernel development and optimization. Distributed training experience is a plus.

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.
  • Validate CUDA kernel outputs and gradients against reference implementations, and benchmark representative shapes, dtypes, and model workloads.

Technical Qualifications

Must-Haves:

  • Strong C++ skills and hands-on CUDA kernel development and optimization for deep-learning workloads.
  • Understanding of GPU memory hierarchy, warp/block execution, and compute-memory trade-offs, with demonstrated profiling-driven optimization.
  • Strong Python skills and experience integrating kernels with PyTorch or an equivalent framework, including numerical and gradient validation where needed.

Nice-to-Haves:

  • Experience with Triton, CUTLASS, or PTX/SASS analysis.
  • Experience with multi-node distributed training or inference systems.
  • Experience validating mixed-precision computations, such as BF16 or FP8.
$150,000 - $450,000 a year
Salary Range
The posted salary range represents the company’s good faith estimate of the compensation for this position upon hire. The actual compensation offered may vary within this range depending on individual qualifications, including but not limited to relevant skills, experience, education, certifications, geographic location, and specific business needs.  
The posted salary range represents the company’s good faith estimate of the compensation for this position upon hire. The actual compensation offered may vary within this range depending on individual qualifications, including but not limited to relevant skills, experience, education, certifications, geographic location, and specific business needs.  
Benefits Include
*Comprehensive medical, dental, and vision benefits 
 *Bonus
*401K Plan
*Generous paid time off, sick leave and holidays
*Paid Parental Leave
*Employee Assistance Program
*Life insurance and disability
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.

Numbers & Facts

LocationSunnyvale, California
Salary$150,000–$450,000 Per Year

Skills

  • Algorithmsunmatched
  • Analysis Skillsunmatched
  • Artificial Intelligence (AI)unmatched
  • Benchmarkingunmatched
  • Best Practicesunmatched
  • C++ Programming Languageunmatched
  • CUDA (Compute Unified Device Architecture)unmatched
  • Code Reviewsunmatched
  • Conferencesunmatched
  • Customer/Client Researchunmatched
  • Data Scienceunmatched
  • Debugging Skillsunmatched
  • Deep Learningunmatched
  • Disability Insuranceunmatched
  • Documentationunmatched
  • GPU (Graphics Processing Unit)unmatched
  • Identify Issuesunmatched
  • Kernel Programmingunmatched
  • Life Insuranceunmatched
  • Machine Learningunmatched
  • Memory Hardwareunmatched
  • Parallel Computingunmatched
  • People Managementunmatched
  • Performance Testingunmatched
  • Performance Tuning/Optimizationunmatched
  • Problem Solving Skillsunmatched
  • Process Improvementunmatched
  • Product Programsunmatched
  • Python Programming/Scripting Languageunmatched
  • Quality Assurance Methodologyunmatched
  • Research Laboratoryunmatched
  • Risk Managementunmatched
  • Scientific Researchunmatched
  • Style Guideunmatched
  • Testabilityunmatched
  • Training/Teachingunmatched
  • Workload Automationunmatched

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