NVIDIA
Posted 46 days agoVerified live 7h ago
Deep Learning Compiler Engineer
Brief overview
Remote
UndergradOr in progress
$152k–$242k/yrStated range
3+ yrsMinimum
4,626 H-1B approvalsDept. of Labor
1,242 green cardsCertified filings
Compiler OptimizationPerformance AnalysisRepresentation (IR) DesignC/C++Software DesignDebuggingTest DesignCPU/GPU ArchitectureCUDAOpenCLMLIRLLVMXLATVMDeep Learning Models and Algorithms
About the company
NVIDIAnvidia.com
NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI.
Visa sponsorship history
4 years sponsoring, last filed FY2026H-1B dependent
Data powered by U.S. Department of Labor. This does not guarantee sponsorship for this specific role.4,626H-1B approved
99%approval rate
1,238new H-1B hires
1,242PERM certified
$190,000median wage / yr
H-1B Petition ApprovalsVisas USCIS actually granted: the strongest sign the company sponsors.
2023997
20241,519
20251,767
2026343
LCA Certified ApplicationsAn early filing step, not a visa approval: it signals intent, not confirmed sponsorship.
2023203
2024276
2025466
2026436
Green Card (PERM) FilingsCertified green card filings: a long-term commitment to international hires.
2023362
2024279
2025573
202628
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Job description
Summary
NVIDIA is a technology company focused on computer graphics, gaming, accelerated computing, and artificial intelligence. The Deep Learning Compiler Engineer will work on the CUDA Tile team to design compiler transformations, develop MLIR-based dialects and lowering passes, and optimize tile-based kernels across NVIDIA GPU architectures.
Responsibilities
- In this role, you will be working on CUDA Tile, a new tile-based programming model for our GPUs. CUDA Tile shipped with CUDA 13.1 and is a major addition to CUDA (https://developer.nvidia.com/cuda/tile). You will design and implement compiler transformations, develop MLIR-based dialects and lowering passes, and optimize the performance of tile-based kernels to ensure they execute efficiently across multiple generations of NVIDIA GPU architectures. The scope of these efforts includes defining public APIs, crafting and implementing compiler and optimization techniques, performance optimization, and other general software engineering work
Skills
- Bachelors, Masters or Ph.D. in Computer Science, Computer Engineering or a related field (or equivalent experience)
- 3+ years of relevant work or research experience in compiler optimization, performance analysis and IR design
- Ability to work independently, define project goals and scope, and lead your own development effort
- Excellent C/C++ programming and software design skills, including debugging, performance analysis, and test design
- Strong interpersonal skills are required along with the ability to work in a dynamic product-oriented team
- Knowledge of CPU and/or GPU architecture. CUDA or OpenCL programming experience
- Experience with the following technologies: MLIR, LLVM, XLA, TVM and deep learning models and algorithms
Qualifications
Must Haves
- Bachelors, Masters or Ph.D. in Computer Science, Computer Engineering or a related field (or equivalent experience)
- 3+ years of relevant work or research experience in compiler optimization, performance analysis and IR design
- Ability to work independently, define project goals and scope, and lead your own development effort
- Excellent C/C++ programming and software design skills, including debugging, performance analysis, and test design
- Strong interpersonal skills are required along with the ability to work in a dynamic product-oriented team
Nice to Haves
- Knowledge of CPU and/or GPU architecture. CUDA or OpenCL programming experience
- Experience with the following technologies: MLIR, LLVM, XLA, TVM and deep learning models and algorithms
Benefits
- Equity
- Comprehensive benefits package
