Virtual Statistical Validation Engineer

Stellantis

Mission Description

As the world is evolving to be connected, Stellantis recognizes that technology is going to disrupt the automotive industry significantly in the next decade. Our organization is seeking high potential, technology game changers to digitally transform the company with a focus on the customer experience.

Stellantis's Software Organization (SWx) was established to build the most captivating experiences in the latest frontiers of Automotive Technology. As part of that foundation we are investing to rapidly grow our capabilities within the field of Automated Driving. We are seeking an Automated Driving Virtual Validation engineer working on Statistical Validation and Functional Reprocessing for L2-L3 test activities.

Statistical Validation is a new branch of Core SW Virtual V&V that is out to validate the Statistical requirements of L2+/L3 features. In Statistical Validation, it is expected to identify the requirements that need to be tested with a variation of different input parameters and create the Logical Scenarios to evaluate the requirements. In this area we require an engineer with a background in computer science focusing on simulations in ADAS/AD and preferably, with a demonstrated knowledge of Validation Process. The nominated engineer will have a chance to collaborate with a global team working on a very new and challenging task to discover the Statistical Validation and Functional Reprocessing areas.

The ideal candidate for this position is a self-productive person who can create the test cases in statistical validation and validate it through local simulations and the toolchains. He/she will need to be able to write the test cases in python and debug and resolve the test issues with required tools. He/she will need to evaluate the new possible pipelines entering the company. He/she must provide structured feedback to the team lead and support the team for resolving the problems for new statistical test cases.

Profile

Basic Qualifications:

Bachelor of Science in Computer Science, Electrical, Mechanical Engineering or equivalent engineering degree from an ABET accredited university
2 or more years of experience in software DevOps or CI/CD
Proved experience using simulators or commercial simulation tools for ADAS/AD,
3 years of proactive coding experience in C++, Python
Demonstrated knowledge about software testing toolsets and languages.


Preferred Qualifications:

Master of Science in Computer Science, Electrical, Mechanical Engineering or equivalent engineering degree from an ABET accredited university
Demonstrated knowledge of ADAS/Autonomous Driving features and relative electronic architectures
Demonstrated knowledge of Json , OpenScenario and OpenDrive Scenario files
Experience in using the simulator's API using python to interact with the simulator
Demonstrated knowledge of test platforms such as Software and Hardware in the Loop
3 or more years of experience in AD scenario based simulation, either based on open source
Familiar with software DevOps or CI/CD environment and test tools: Docker, Airflow, Jenkins
Experience in C++ and QEMU emulation test
Demonstrated Knowledge of Matlab/simulink Carsim,