NVIDIA

4 weeks ago

Deep Learning Applications Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 3 hours agoStatus: Live

Job Summary

Design and deploy agentic AI systems for autonomous driving, developing LLM/VLM-powered agents, deep learning models for robotics and ADAS, and workflows to productize driver assistance capabilities. Collaborate with solutions architecture, validation, firmware, and customer-facing teams to move features from prototype through SIL/HIL toward production readiness, applying hands-on experience with automotive embedded platforms and AI/ML tooling.

Location: Seoul

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Design and deploy LLM/VLM-powered agents for use cases across the autonomous driving stack, including automated bug diagnosis and triaging flows.
•Develop and optimize innovative deep learning models for robotics and ADAS systems.
•Build workflows, models, and simulations to productize NVIDIA driver assistance capabilities.
•Develop agentic workflows for SIL and HIL solutions and integrate them with validation and test infrastructure.
•Collaborate with solutions architecture, validation, firmware, and customer-facing teams to deliver features from prototype through SIL/HIL toward production readiness.

Key Requirements

•2+ years of professional software engineering experience
•BS/MS in Computer Engineering, Computer Science, Electrical Engineering, Robotics, or related field (or equivalent experience)
•Hands-on experience on embedded systems in automotive-related platforms (ECU/SoC stacks, ADAS, AUTOSAR/Linux-based software, SIL/HIL, OEM/Tier-1 environments)
•Strong proficiency in Python (agent orchestration, tooling, data pipelines) with working proficiency in C/C++ to read embedded code and logs
•Practical experience with Git, Docker, CI/CD, and test or verification frameworks used for automated software validation

Experience:2+ yearsAutomotiveADASEmbedded systemsAI/MLRobotics

Education:Bachelor's in Computer Engineering / Computer Science / Electrical Engineering / Robotics

Skills:PythonC++GitDockerCI/CDLLM APIsAgent frameworksLog analysisEmbedded systemsAutomationTesting

Tech Stack:PythonC++LangChainAutoGenCrewAIDockerGitCI/CDSILHILEmbedded Linux

Company Brief

NVIDIA

Designs and manufactures GPUs, AI accelerators, and system-on-chip products for gaming, data centers, professional visualization, and automotive markets, enabling advanced graphics, AI, and high-performance computing solutions worldwide.

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor

Loading job details...

Preparing the role view and application actions.

NVIDIA

4 weeks ago

Deep Learning Applications Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 3 hours agoStatus: Live

Job Summary

Location: Seoul

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Design and deploy LLM/VLM-powered agents for use cases across the autonomous driving stack, including automated bug diagnosis and triaging flows.
•Develop and optimize innovative deep learning models for robotics and ADAS systems.
•Build workflows, models, and simulations to productize NVIDIA driver assistance capabilities.
•Develop agentic workflows for SIL and HIL solutions and integrate them with validation and test infrastructure.
•Collaborate with solutions architecture, validation, firmware, and customer-facing teams to deliver features from prototype through SIL/HIL toward production readiness.

Key Requirements

•2+ years of professional software engineering experience
•BS/MS in Computer Engineering, Computer Science, Electrical Engineering, Robotics, or related field (or equivalent experience)
•Hands-on experience on embedded systems in automotive-related platforms (ECU/SoC stacks, ADAS, AUTOSAR/Linux-based software, SIL/HIL, OEM/Tier-1 environments)
•Strong proficiency in Python (agent orchestration, tooling, data pipelines) with working proficiency in C/C++ to read embedded code and logs
•Practical experience with Git, Docker, CI/CD, and test or verification frameworks used for automated software validation

Experience:2+ yearsAutomotiveADASEmbedded systemsAI/MLRobotics

Education:Bachelor's in Computer Engineering / Computer Science / Electrical Engineering / Robotics

Skills:PythonC++GitDockerCI/CDLLM APIsAgent frameworksLog analysisEmbedded systemsAutomationTesting

Tech Stack:PythonC++LangChainAutoGenCrewAIDockerGitCI/CDSILHILEmbedded Linux

Company Brief

NVIDIA

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor