Senior Software Control Integration Engineer - Autonomous Vehicles
NVIDIA is hiring a Senior Software Control Integration Engineer - Autonomous Vehicles in Santa Clara, United States. It pays $184k-$288k a year and Level rates it ; you can apply on NVIDIA.
Level's read on this job
- Level rates this role Builds AI ●●●●: the job is building AI systems.
- Tools and skills the posting cites include computer vision, NLP and speech.
- Level classifies it as a senior role.
- Level lists 2,700+ other open roles at NVIDIA.
AI in this role
We are now looking for a Senior Software Autonomous Vehicle Control Integration Engineer. As a Senior Software Control Integration Engineer, you will work on state-of-the-art autonomous vehicle technologies with leaders in AI / deep learning, computer vision, and vehicle control.
You will be responsible for developing, maintaining and integrating autonomous auto control algorithms and software. You will develop solutions for vehicle trajectory tracking, model predictive control, and vehicle state estimation. You should have strong analytical skills, good communication, and interpersonal capabilities to work in a team and make a joint effort towards a common goal. Prior knowledge about vehicle control, vehicle ECU, Drive-by-Wire systems, and in-vehicle network and autonomous vehicles are highly valued.
What you’ll be doing:
Contribute to the development related to vehicle dynamics and control and support other teams in such areas, e.g. ACC/LK, urban driving, trajectory planning, vehicle operation limit estimation, emergency maneuvers (collision avoidance, mitigation), etc.
Design technologies needed to build Autonomous Vehicle software stack, write new software modules from scratch that drive our vehicles.
Provide feedback for overall system design to product level: system architecture, failure mode, system redundancy, etc.
Build new performance offline and online benchmarks for vehicle control.
Define and build tools to tune our vehicle dynamics control and manage calibration updates for various vehicle types.
Drive integration efforts of control functionality across different platforms, support troubleshooting of control and actuation issues in vehicles.
Develop and maintain vehicle test suites to detect control integration problems, develop and maintain automated tests to ensure SW quality and prevent regressions.
Most importantly, work on groundbreaking and innovative technology, tackle difficult problems, and help build a world-class system!
What we need to see:
BS, MS, or higher degree in Mechanical Engineering, Electrical Engineering, Computer Science or equivalent experience
8+ years of work experience in relevant fields
Knowledge and hands-on application background in control theories, including at least three of the following fields: classical control, modern control, nonlinear control, MPC, optimal control, robust control, sliding mode control.
Understanding of state estimation techniques such as Luenberger observer, kalman filter, etc.
Ability to develop vehicle models and perform parameter identification and benchmarking.
Knowledge of high-level algorithm design and prototyping in simulation environments (Matlab/Simulink/Python) to product oriented implementation with C/C++.
Experience in architectural design and software development with C/C++ for real-time embedded control systems, such as vehicle ECU systems.
Understanding of test and verification methodologies for automotive software, know-how in writing unit and system level tests.
Experience of integrating, tuning, and validating prototype and/or production control software with application, driver, and vehicle network layers.
Experience of development and/or usage of in-vehicle control software verification and calibration tools for autonomous vehicle applications.
Ways to stand out from the crowd:
Hands-on experience in autonomous vehicle or advanced driver assist system development such as lane keeping, adaptive cruise control, etc.
Background in automotive safety concept, failure mode, common analysis tools such as FMEA
Experience in developing and launching vehicle safety critical control system products such as powertrain, steering system, brake system, advanced driver assist system, etc.
Understanding of deep learning and neural network concepts
12+ years engineering experience at automotive OEM, tier-1 supplier or autonomous driving start-ups
PhD with relevant experience
Academic and commercial groups around the world are powering a revolution in artificial intelligence using deep learning techniques running on NVIDIA GPUs, enabling breakthroughs in problems from image classification to speech recognition to natural language processing. Intelligent machines powered by AI computers that can learn, reason and interact with people are no longer science fiction. Today, a self-driving car powered by AI can meander through a country road at night and find its way. An AI-powered robot can learn motor skills through trial and error. This is truly an extraordinary time. The era of AI has begun.
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: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 November 3, 2026.This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive 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.How we rate this
Senior Software Control Integration Engineer - Autonomous Vehicles at NVIDIA rates 86 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
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- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
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- Walk me through a computer vision problem you solved, from raw data to a deployed model.
- What NLP problem have you worked on, and how did you measure whether it actually worked?
- What have you built with speech recognition or text-to-speech, and where did it break?
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- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
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