Deep Learning Software Engineer, Inference - New College Grad 2026 at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Entry Level & New GradExperience Level

Full TimeJob Type

UnknownVisa

AI, TechnologyIndustries

Requirements

Pursuing a Masters or PhD or equivalent experience in relevant field (Computer Engineering, Computer Science, EECS, AI)
C/C++ programming and software design skills
SW Agile skills are helpful and Python experience is a plus
Experience with training, deploying or optimizing the inference of DL models in production is a plus
Modeling, profiling, debug, and code optimization or architectural knowledge of CPU and GPU is a plus
GPU programming experience (CUDA, OAI TRITON or CUTLASS) is a plus
Ways to Stand out from The Crowd
Contribute to deep learning software projects, such as PyTorch, vLLM, and SGLang to drive advancements in the field
Experience with Multi GPU Communications (NCCL, NVSHMEM)

Responsibilities

Performance optimization, analysis, and tuning of DL models in various domains like LLM, Multimodal and Generative AI
Scale performance of DL models across different architectures and types of NVIDIA accelerators
Contribute features and code to NVIDIA’s inference libraries, vLLM and SGLang, FlashInfer and LLM software solutions
Work with cross-collaborative teams across frameworks, NVIDIA libraries and inference optimization innovative solutions

Skills

Key technologies and capabilities for this role

C++PythonDeep LearningInference OptimizationGPU ProgrammingCUDACUTLASSTritonNCCLvLLMSGLangFlashInferPerformance TuningProfilingLLMGenerative AI

Questions & Answers

Common questions about this position

What is the salary range for this position?

The base salary range is 120,000 USD - 189,750 USD for Level 2, and 148,000 USD - 235,750 USD for Level 3, determined based on location, experience, and pay of employees in similar positions.

What benefits are offered?

NVIDIA offers a comprehensive benefits package along with equity eligibility.

Is this a remote position or does it require working in an office?

This information is not specified in the job description.

What skills are required for this role?

Candidates must be pursuing a Masters or PhD in Computer Engineering, Computer Science, EECS, or AI, with C/C++ programming and software design skills; Python, SW Agile skills, DL model experience, GPU programming (CUDA, OAI TRITON, CUTLASS), and CPU/GPU optimization knowledge are pluses.

How can I stand out as a candidate?

Stand out by contributing to deep learning software projects like PyTorch, vLLM, and SGLang, or having experience with Multi GPU Communications such as NCCL or NVSHMEM.

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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