Senior System Software Engineer - AV Platform
Overview
- Added in 30 days
- 658
- At this company, still open
Skills named in this posting
- C++
- Python
The Autonomous Vehicles Platform team is looking for a hands-on System Software Engineer. As part of our team, you will work on our Autonomous Driving Platform software, implementing performant and scalable solutions for data collection and autonomous vehicle fleets. Our team is responsible for developing platform and middleware features for self-driving cars. This includes software that interacts with various sensors including Cameras, LIDAR, RADAR, GPS, IMU, Vehicle CAN etc.
We are seeking candidates with interests in inventing, developing, and maintaining application framework and tools on multi-computer and heterogeneous architectures. The role encompasses working with various teams across the stack, from platform and embedded software to cloud infrastructure, underpinned by safety and performance. It extends an opportunity to contribute to the technology that will drive the cars of the future!
What you'll be doing:
• Integrating sensors into our AV driving software stack.
• Develop and improve startup user experience of our AV stack.
• Work on areas such as sensor abstraction layers, data processing & performance optimization, data serialization, and service frameworks.
• Collaborate with hardware, platform software, product, safety, performance, algorithms and cloud teams.
What we need to see:
• BS or MS degree in Computer Science, Electrical Engineering, or related field (or equivalent experience).
• 8+ years of professional experience working on system software.
• Excellent programming skills in C++, C and Python.
• Familiarity with source control tools.
• Solid understanding of Linux, QNX, ROS, and/or real-time operating systems.
• Experience in developing user-space system software, with a willingness to delve into kernel-space and/or low-level hardware when needed.
• Knowledge about embedded system programming, threading, mutex, synchronization, communication, and parallel computing to build highly-scalable and efficient applications.
• Familiarity with hardware architecture for CPU/GPU and memory alongside performance.
• Prior experience working in the following areas: Autonomous Vehicles, Robotics, Self-Driving-Cars, GPU technology, Embedded Systems, Computer Vision.
Ways to stand out from the crowd:
• Deep understanding of system architecture, CPU/GPU/Memory/Storage, everything related to performance optimization.
• Experience in Autonomous Vehicle or Robotic System Building.
• Hands-on experience in embedded development, operating systems and real-time software.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until May 22, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
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Original posting: jobs.nvidia.com
RISC-V ecosystem
NVIDIA Corporation in the RISC-V ecosystem
RISC-V International: Premier Board
Founded in 1993, NVIDIA is an AI computing company. The company is headquartered in Santa Clara, California.
- NVIDIA is bringing CUDA platform support to RISC-V, i.e. allowing a RISC-V CPU to host CUDA GPU applications
- Publicly credited the RVA23 profile as the enabler: "We wouldn't have considered porting CUDA to RISC-V without it"
- Active in RISC-V International profile/standards work and a frequent presence in RISC-V ecosystem coverage
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