NVIDIA
Posted 2 days agoVerified live 15h ago
AI Developer Technology Engineer
Brief overview
Remote
MastersOr in progress
$124k–$196k/yrStated range
1+ yrsMinimum
4,626 H-1B approvalsDept. of Labor
1,242 green cardsCertified filings
C/C++Parallel ProgrammingPerformance Analysis and OptimizationLow-Level Performance OptimizationCPU and GPU ArchitecturesAccelerated ComputingGenerative AI Training and InferenceAlgorithmsLinear AlgebraNumerical Methods
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
Top sponsored roles
Software EngineerHardware Engineer, ElectronicsEngineer Senior Systems SoftwareArchitectEngineer Senior ASIC
Sponsored employees from
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Job description
Summary
NVIDIA develops accelerated computing platforms and software for advanced artificial intelligence and generative AI applications. The AI Developer Technology Engineer will optimize generative AI training and inference workloads, collaborate with developers and internal engineering teams, contribute to software libraries and open-source projects, and share optimization techniques with the broader industry.
Responsibilities
- Develop cutting-edge techniques to GPU-accelerate complex workloads across state-of-the-art generative AI (including LLMs, diffusion models, and multimodal systems), deep learning, and machine learning domains
- Work directly with key developers to optimize and accelerate generative AI training and inference on NVIDIA platform. Build and optimize algorithms to deliver the best performance, and contribute to training and inference frameworks, low-level software libraries, and open-source projects
- Partner directly with top technical experts in industry and academia to perform in-depth analysis and optimization of complex AI algorithms on modern CPU and GPU architectures
- Shape the design of next-generation hardware, system software, libraries, and programming models through tight collaboration with NVIDIA’s internal engineering and research teams
- Share your breakthrough optimization techniques by publishing in developer blogs and presenting at industry conferences
Skills
- MS in Computer Science, Computer Engineering, or related computational field (or equivalent experience)
- 1+ years of relevant work or research experience in software engineering and performance tuning
- Programming fluency in C/C++ with a deep understanding of algorithms and software development
- A background in accelerated computing, with comprehensive knowledge of parallel programming, performance analysis and optimization
- Hands on experience doing low-level performance optimizations
- Foundational understanding of modern CPU and GPU architectures
- Good communication and organization skills, with a logical approach to problem solving, and prioritization skills
- PhD in a relevant field
- Experience with training and inference stacks, serving frameworks, pre-training and post-training pipelines
- Strong foundation in linear algebra and numerical methods
Qualifications
Must Haves
- MS in Computer Science, Computer Engineering, or related computational field (or equivalent experience)
- 1+ years of relevant work or research experience in software engineering and performance tuning
- Programming fluency in C/C++ with a deep understanding of algorithms and software development
- A background in accelerated computing, with comprehensive knowledge of parallel programming, performance analysis and optimization
- Hands on experience doing low-level performance optimizations
- Foundational understanding of modern CPU and GPU architectures
- Good communication and organization skills, with a logical approach to problem solving, and prioritization skills
Nice to Haves
- PhD in a relevant field
- Experience with training and inference stacks, serving frameworks, pre-training and post-training pipelines
- Strong foundation in linear algebra and numerical methods
Benefits
- You will also be eligible for equity.
- Hybrid work arrangement
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