Senior Deep Learning Software Engineer, Inference and Model Optimization
$184k - $357k • Remote • US, CA, Santa Clara
Posted 10d ago
Job Location
US, CA, Santa Clara
Tech Stack
Remote Work Policy
Fully remote
Categories
LLM Engineer
About the job
NVIDIA is seeking a Senior Deep Learning Software Engineer to join their Algorithmic Model Optimization Team. This role focuses on optimizing generative AI models, including LLMs and diffusion models, for maximum inference efficiency. The team utilizes techniques like neural architecture search, pruning, sparsity, and quantization, and develops an innovative software platform for automated deployment. The engineer will contribute to applied research and the development of this software, which is used both internally at NVIDIA and externally by other AI development teams. This is an opportunity to push the boundaries of inference efficiency and large-scale automated deployment, working with high-level frameworks and improving high-performance kernel implementations.
Responsibilities
- Train, develop, and deploy generative AI models like LLMs and diffusion models using NVIDIA's AI software stack.
- Leverage and build upon the torch 2.0 ecosystem to analyze and extract standardized model graph representations for automated deployment.
- Develop high-performance optimization techniques for inference, including automated model sharding and efficient attention kernels.
- Collaborate with internal teams to integrate performant kernel implementations into the automated deployment solution.
- Analyze and profile GPU kernel-level performance to identify optimization opportunities.
- Innovate on inference performance to maintain and increase market leadership for NVIDIA's inference software solutions.
- Architect and design a modular and scalable software platform to enhance user experience and broaden model support.
Requirements
- Master's, PhD, or equivalent experience in Computer Science, AI, Applied Math, or related field.
- 8+ years of relevant work or research experience in Deep Learning.
- Excellent software design skills, including debugging, performance analysis, and test design.
- Strong proficiency in Python, PyTorch, and related ML tools (e.g., HuggingFace).
- Strong algorithms and programming fundamentals.
- Good written and verbal communication skills.
- Ability to work independently and collaboratively in a fast-paced environment.
Benefits
- Highly competitive salaries
- Comprehensive benefits package
- Eligibility for equity
- Eligibility for benefits