About the role
We are looking for a highly motivated Software Engineer to join its multi-layered, collaborative and fast-paced customer interfacing organization. In this role, you will be supporting our customers closely to adopt NVIDIA’s DRIVE OS software stack to the program requirements. This position requires a deep understanding of BSP, operating systems and device drivers, a strong experience in software development, ECU bring-up, profiling and debug, as well as excellent customer-facing and great teammate.
What you’ll be doing:
Support the DRIVE OS part of the NVIDIA’s autonomous driving software stack.
System & Vehicle Integration - Architecture & infrastructure for benches, HILs, SIL, Vehicle readiness for DC and Vehicle readiness for Function bringup
Work closely with internal software groups to understand the requirements, design and implementation of the base software layer (Linux/QNX OS and device driver components).
Support OEM customers to port DRIVE OS to their HW platform and ensure the program requirements and criteria are met.
What we need to see:
Degree from a leading university or equivalent experience in an engineering or computer science related field (BS; MS or PhD preferred).
5+ years of work experience in software development.
Fundamental knowledge on SoC architectures and on-chip components.
Understanding of autonomous vehicle system with sensors
Strong knowledge of C/C++/Python, QNX and/or Linux OS.
Understanding of CPU/GPU architectures, data structures, OS internals, multi-threading, inter-process communications, memory management techniques.
Extensive hands-on experience in BSP porting and device driver internals.
Knowledge and experience working in Multicore/heterogenous SoCs, camera/imaging/video/graphics/compute system.
Prior experience of working in software development in complex automotive systems.
Excellent communication and organization skills, with a logical approach to problem solving, good time management and task prioritization as well as interpersonal skills.
Willingness to travel around worldwide to support NVIDIA partners.
Ways to stand out from the crowd:
Experience with QNX OS for Safety (QOS).
Experience with autonomous vehicle system integration.
Experience with Automotive SPICE and/or ISO26262 standards.
Extensively supported customers both onsite and offsite.
Self-motivated and work effectively across different functional teams.
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative, hardworking and proactive, we want to hear from you! NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services.
Aplyr's read
NVIDIA is a pioneering force in GPUs and AI, attracting top talent in engineering and innovation-driven roles across various tech domains.
What's promising
- •NVIDIA leads the GPU market, crucial for gaming and AI applications.
- •The company invests heavily in AI and deep learning, driving technological advancements.
- •NVIDIA's strong market position offers stability and growth opportunities for employees.
What to watch
- •High competition in the semiconductor industry can impact market share.
- •Rapid technological changes require constant adaptation and learning.
- •Intense workload and high expectations may affect work-life balance.
Why NVIDIA
- •NVIDIA's GPUs are industry benchmarks in gaming and professional graphics.
- •The company's AI research is at the forefront of deep learning innovation.
- •NVIDIA's culture emphasizes cutting-edge technology and engineering excellence.
Aplyr’s read is generated by AI from public sources. Was it useful?
About NVIDIA
NVIDIA is a leading technology company known for its graphics processing units (GPUs) for gaming and professional markets, as well as its advancements in artificial intelligence and deep learning.
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