Senior System Software Engineer - Autonomous Vehicles Platform 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, AutomotiveIndustries

Requirements

4+ years of relevant industry experience
BS/MS or higher or equivalent experience in computer engineering, computer science or related engineering disciplines
Excellent C and C++ programming skills
Experience developing and debugging multithreaded/distributed applications like multimedia systems, game engines, etc
Strong knowledge of programming and debugging techniques, especially for parallel and distributed architectures
Strong knowledge on Linux, QNX, and/or other real-time operating systems
Experience with frameworks for robotics such as ROS and/or for multimedia such as GStreamer
Thrive on writing low latency, highly performant code
Great communication and analytical skills
Ways to stand out (Preferred)
Understanding of embedded architectures
Experience developing software in heterogeneous architectures, including GPUs
Knowledge of automotive systems, notably ADAS applications
Software development for modern OpenGL (Core Profile) and Linux
Experience with version control systems GIT and build system like CMake/Bazel

Responsibilities

Developing and optimizing software architecture and frameworks for real-world performance while matching or exceeding customer requirements
Working on areas such as component abstraction layers, inter-process data sharing and communication, and process scheduling
Developing efficient mechanisms to maximize utilization on computers with multiple heterogeneous hardware engines
Solidifying existing frameworks and software components, and validate with large amounts of real and synthetic data for the improvements of the computational performance and system utilization
Performing in-vehicle tests, collecting data, and completing autonomous drive missions
Developing unit tests, documentation for features, 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

C++

CUDA

GPGPU

Multithreading

Distributed Applications

Software Architecture

Process Scheduling

MISRA

Unit Testing

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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