Senior System Software Engineer, Deep Learning at NVIDIA

Seoul, South Korea, South Korea

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

AutomotiveIndustries

Requirements

BS/MS or higher degree in Computer Science, Computer Engineering or Electrical Engineering
Experience in developing or using deep learning frameworks (e.g. TensorFlow, Keras, PyTorch, Caffe, ONNX, etc.)
5+ years of experience in optimizing DNN Layers for GPU or other DSPs
Proficiency in C and C++ and Data Structures
Strong OS fundamentals and knowledge of CPU/GPU architecture
Familiar with state-of-the-art CNN/LSTM/Transformers architecture
Ways to stand out (Preferred)
Strong analytical and problem solving skills, with good attention to details
Background with NVIDIA software libraries such as CUDA and TensorRT
Experience in automotive development processes like ASPICE or ISO26262
Excellent communication and organization skills, good time management and task prioritization
Open source project ownership or contribution, GitHub repositories, guiding and/or mentoring experience
Understanding of the DRIVE or NVIDIA GPU hardware

Responsibilities

Develop solutions around NVIDIA GPU and Deep learning accelerators to realize DNNs for ADAS Systems
Optimize DNNs for the GPU and other hardware accelerators like DLA using CUDA/TensorRT
Improve DNN architectures using ML algorithms on NVIDIA GPUs or DLAs
Conduct benchmarking and evaluation activities to continuously improve inference latency, accuracy and power consumption of DNNs
Stay up to date with the latest research and innovations in deep learning, implement and experiment with new ideas to improve NVIDIA's automotive DNNs
Responsible for the technical relationship and assisting the automotive customer in building creative solutions based on NVIDIA technology
Collaborate with engineering teams in our US, APAC, India and Europe locations

Skills

Key technologies and capabilities for this role

CUDATensorRTTensorFlowPyTorchC++CONNXKerasCaffeCNNLSTMTransformersGPUDLAADAS

Questions & Answers

Common questions about this position

What education and experience are required for this Senior System Software Engineer role?

A BS/MS or higher degree in Computer Science, Computer Engineering or Electrical Engineering is required, along with 5+ years of experience in optimizing DNN Layers for GPU or other DSPs, proficiency in C and C++ and Data Structures, strong OS fundamentals, and knowledge of CPU/GPU architecture.

What are some ways to stand out as a candidate for this position?

Candidates can stand out with strong analytical and problem solving skills, background with NVIDIA software libraries such as CUDA and TensorRT, experience in automotive development processes like ASPICE or ISO26262, excellent communication skills, open source contributions, and understanding of DRIVE or NVIDIA GPU hardware.

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

This information is not specified in the job description.

What is the salary or compensation for this role?

This information is not specified in the job description.

What is the company culture like at NVIDIA?

NVIDIA has forward-thinking and hardworking people, values creative, hardworking, and proactive individuals, and is considered one of the technology world’s most desirable employers, with teams collaborating across US, APAC, India, and Europe locations.

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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