Deep Learning Performance Architect

1 month ago


San Francisco, California, United States Genmo Full time
Role Overview:

At Genmo, we're dedicated to pushing the boundaries of video generation in AGI. As a Deep Learning Performance Engineer, you'll play a crucial role in optimizing the performance of our large generative AI models. Your expertise will ensure that our models run efficiently on clusters, leveraging advanced techniques and tools to enhance their performance.

Key Responsibilities:

• Analyze and optimize the performance of massively parallel and distributed systems
• Implement and fine-tune distributed training strategies for multi-GPU and multi-node environments
• Implement high-performance CUDA, Triton, C++ and PyTorch code
• Profile model performance and identify bottlenecks using tools like NVIDIA NSight Systems, PyTorch Profiler, and TensorFlow Profiler
• Develop and maintain benchmarking suites for continuous performance monitoring
Qualifications:

• Master's or PhD in Computer Science, Electrical Engineering, or a related field
• 5+ years of experience in optimizing deep learning models, preferably in a production environment
• Must have strong programming skills in Python and C++. Experience in training large models using Python & PyTorch and/or TensorFlow including their distributed training frameworks.
• Proven track record of optimizing large-scale models (10B+ parameters)
• Deep understanding of GPU architecture and CUDA programming
• Experience in entire development pipeline from data processing, preparation & data loading to training and inference.
• Experience optimizing and deploying inference workloads for throughput and latency across the stack (inputs, model inference, outputs, parallel processing etc.)
• Demonstrated expertise in high-performance computing using NVIDIA Triton and CUDA
• Demonstrated ability to significantly improve model inference and training speeds through low-level optimizations

Ideal Candidates:

• Knowledge of distributed inference systems for handling high-volume workloads
• Strong background in linear algebra, optimization, and machine learning algorithms
• Experience with generative AI models (GANs, Diffusion Models, Transformers)
• Knowledge of hardware-aware neural architecture design
• Experience with high-performance computing (HPC) environments
• Contributions to relevant open source projects or research publications
• Genmo is an Equal Opportunity Employer. Candidates are evaluated without regard to age, race, color, religion, sex, disability, national origin, sexual orientation, veteran status, or any other characteristic protected by federal or state law.

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