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NVIDIA

Designs the chips and software that power AI

Senior Systems Engineer - Autonomous Driving

Aerospace EngineeringConfirmed live in the last 24 hours
Full-timeRemote

About the Job

Requirements

  • A Master of Science or PhD in Engineering, Physics, Computer Science, or a related field, or equivalent experience.
  • At least 8 years of experience in safety-critical systems engineering, system analysis, data analysis, and software architecture.
  • A strong software development background and proven coding skills.
  • Hands-on experience in SOTIF analysis (ISO 21448), functional safety (ISO 26262), and multi-functional architectural trade-off analysis.
  • An understanding of trade-offs between end-to-end deep learning approaches, classical modular perception and planning stacks, and associated validation and test strategies.

Responsibilities

  • Develop use cases and system requirements for L3 and L4 autonomous driving products based on customer needs, traffic regulations, certification standards, and industry guidelines.
  • Perform system-level analysis to define performance requirements and allocate performance budgets across subsystems.
  • Formulate test cases and define critical performance metrics to ensure compliance with functional and safety requirements.
  • Define and drive online and offline test strategy and execution at vehicle and component levels.
  • Partner with Data Analytics, Test Engineering, and System Integration & Test teams to develop evaluators and important metrics, prove datasets cover sufficient scenarios and requirements, and target appropriate sampling strategies through data collection and real-world driving.
  • Establish cross-functional relationships with collaborators across engineering, safety, validation, and product teams.
  • Drive innovation in requirements decomposition, traceability, and verification processes.
  • Promote and cultivate a strong systems engineering approach across the organization.

Desired Qualifications

  • Experience contributing to a launched L3/L4 autonomous vehicle program.
  • Experience in AI safety and safety validation for machine-learning-based systems.
  • Hands-on experience with large-scale datasets, data science, and analytics workflows.
  • Strong software engineering experience with proficiency in Python, SQL, and C++.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

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