Research Scientist, Efficient Deep Learning - New College Grad 2025 at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Entry Level & New GradExperience Level

Full TimeJob Type

UnknownVisa

Technology, AI, Machine LearningIndustries

Requirements

Completing or recently completed a Ph.D. in Computer Science/Engineering, Electrical Engineering, etc., or equivalent research experience
Excellent knowledge of theory and practice of computer vision methods, as well as deep learning
Background in pruning, quantization, NAS, efficient backbones, and so on (plus)
Experience with large language models and large vision-language models (required)
Excellent programming skills in Python and PyTorch; C++ and parallel programming (e.g., CUDA) (plus)
Hands-on experience with large-scale model training including data preparation and model parallelization (tensor and pipeline) (required)
Outstanding research track record
Excellent communication skills

Responsibilities

Research, design and implement novel methods for efficient deep learning
Publish original research
Collaborate with other team members and teams
Mentor interns
Speak at conferences and events
Work with product groups to transfer technology
Collaborate with external researchers

Skills

Key technologies and capabilities for this role

Deep LearningComputer VisionPruningQuantizationNASPyTorchPythonC++CUDALarge Language ModelsVision-Language ModelsModel ParallelizationTensor ParallelismPipeline Parallelism

Questions & Answers

Common questions about this position

What is the base salary range for this position?

The base salary range is 160,000 USD - 258,750 USD, determined based on location, experience, and pay of employees in similar positions.

What benefits are offered for this role?

You will be eligible for equity and benefits.

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

This information is not specified in the job description.

What skills and experience are required for this Research Scientist role?

Required qualifications include completing or recently completed a Ph.D. in Computer Science/Engineering or equivalent, experience with large language models and large vision-language models, hands-on experience with large-scale model training including data preparation and model parallelization, excellent Python and PyTorch programming skills, and an outstanding research track record.

What is the team culture like at NVIDIA for this role?

You will work within an amazing and collaborative research team that consistently publishes at top venues, with expertise in computer vision, deep learning, and generative models. NVIDIA has forward-thinking and productive people and values creative and autonomous individuals.

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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