Senior Applications Engineer, GenAI for Science at NVIDIA

Tokyo, Japan

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, Scientific Research, AIIndustries

Requirements

Excellent verbal, written communication, and technical presentation skills in Japanese. Business level English communication is also a requirement
Degree or equivalent experience in Computer Science, Applied Mathematics, or related engineering field (Masters preferred)
5+ years hands-on experience developing, optimizing and running AI/ML models or LLMs using popular frameworks (PyTorch, or similar), and languages (C++, Python)
Deep understanding of Gen AI model architectures (GPT-x, Llama, MoE, etc)
Ability to work independently and as part of a globally distributed team

Responsibilities

Work alongside research teams worldwide adopting NV's GenAI SW for scientific data/models
Debug, profile and recommend optimizations
Provide customer feedback back into engineering teams on improving of NV's GenAI SW for science research and discovery
Participate in Gen AI hands-on hackathons/workshops that drive adoption of NV’s GenAI SW stack in the scientific community

Skills

Key technologies and capabilities for this role

PyTorchPythonC++Generative AIGPTLlamaMoEMachine LearningDeep LearningGPUModel OptimizationProfiling

Questions & Answers

Common questions about this position

What compensation and benefits does NVIDIA offer for this role?

NVIDIA offers competitive salaries and a generous benefits package.

Is this position remote or does it require working in Japan?

This information is not specified in the job description.

What skills are required for the Senior Applications Engineer role?

Required skills include excellent communication and technical presentation skills in Japanese and business-level English, a degree in Computer Science or related field, 5+ years experience with AI/ML models using PyTorch or similar and languages like C++ and Python, and deep understanding of GenAI model architectures.

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

The team consists of forward-thinking and hardworking people in rapidly growing exclusive engineering teams, working with top researchers worldwide in a globally distributed environment.

What makes a candidate stand out for this position?

Candidates stand out with expertise in deploying large-scale training and inferencing pipelines, hands-on experience customizing AI models for multi-modal scientific data, contributions to research papers or open-source GenAI projects, and experience with complex workflows on large-scale HPC systems.

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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