Senior Integration Engineer - Autonomous Vehicle at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Autonomous Vehicles, Artificial Intelligence, AutomotiveIndustries

Requirements

BS/MS or higher in computer engineering, computer science or related engineering fields, or equivalent experience
5+ years of relevant industry experience
Excellent C and C++ programming skills
Experience developing and debugging multithreaded/distributed applications like multimedia systems, game engines, etc
Profound knowledge of programming and debugging techniques
Experience developing software in heterogeneous architectures, including GPUs
Knowledge of image processing APIs (e.g. OpenCV) and MATLAB tools, automotive systems, notably ADAS applications
Software development for CUDA, Linux, and QNX
Experience with version control systems GIT and build system like CMake/Bazel
Be hands-on and work well within a team of algorithm, software and hardware engineers, with a significant level of detail orientation and a penchant for data organization and presentation
Solid understanding of Linux, Android, and/or other real-time operating systems

Responsibilities

Defining functional software architecture for NVIDIA's L2/L3/L4 autonomous driving solutions
Integrating modular software components (e.g. perception, planning, etc.) together to implement customer-required self-driving functions
Optimizing product implementation to achieve target performance goals
Diagnosing system software & functional driving issues reported on target driving platforms, including on-road & simulation
Developing efficient mechanisms to improve utilization on computers with multiple heterogeneous hardware engines
Performing in-vehicle tests, collecting data and completing autonomous drive missions
Developing system tests, documentation of product functions, evaluating quality and proposing corrective actions
Developing highly efficient product code in C++, making use of high algorithmic parallelism offered by GPGPU programming (CUDA)
Follow quality and safety standards such as defined by MISRA

Skills

Software Architecture

System Integration

Perception

Planning

Performance Optimization

Debugging

Autonomous Driving

GPU

Deep Learning

Heterogeneous Hardware

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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