The Automated Driving Advanced Development team is actively searching for a Sensor Modeling & Simulation Engineer. This is a sensor systems engineering position with a focus on modeling & simulation. You will act as a subject matter expert in the sensing domain, providing tools and expertise to internal customers to enable integration of sensors within Stellantis vehicles, electrical architectures, and ADAS/AD features. With your strong knowledge of the fundamentals of electromagnetic radiation and its interaction with the world, you will build tools to simulate sensor performance, sensor coverage, and model sensing requirements. You will test your models against real world data to refine them and make recommendations to the requirements engineers. You will also work with the Software-in-Loop and Data Science teams to develop/integrate sensor models and process data collected from test vehicles.
The main job responsibilities will be:
- Develop modeling & simulation tools and concepts for active and passive sensing systems from first principles
- Sensor Coverage Map: Maintain sensor coverage map for STELLANTIS sensor configurations based on sensor simulation data and update as real world data is collected
- KPI Calculation Methods: Define calculation methods for sensor Key Performance Indicators, and facilitate internal customer in implementation of these calculations
- Benchmarking:
- Construct analytical test plans for benchmarking sensors with respect to both feature level and sensor level specifications and KPIs
- Collect data from sensors within the Stellantis portfolio and from prospective new suppliers
- Lead the instrumentation of benchmarking vehicles to integrate sensors under test
- Analyze data and prepare conclusions / reports
- Sensor Models for SIL/HIL/MIL: Define requirements for the sourcing/internal development of simulation models of component performance at an appropriate level of fidelity for internal customer use cases (e.g. MIL, SIL, HIL)
- Advise production, development and software teams on active and passive sensor physics, packaging/integration, production, data analysis, data processing and fusion.
Basic Qualifications
- Education: Bachelor's degree in Engineering from an ABET accredited program
- 1 year of Engineering experience
- Strong knowledge of engineering physics, including the equations of motion, electricity and magnetism, and light
- Theoretical background in optical and RF sensing link budget calculation
- Practical real world experience working with automotive ADAS/AD sensors particularly camera, radar, and lidar
- Basic knowledge about the automotive development process
- Strong knowledge of programming for engineers such as Python or MATLAB
- Strong understanding of statistics
- Basic understanding of Ethernet and CAN networking
- Basic knowledge of Driver Assistance systems, such as:
- Longitudinal control systems (Autonomous Emergency braking and Forward Collision Warning, Adaptive Cruise Control, Intelligent Speed Assistance)
- Lateral control systems (Lane Departure Warning and Lane Keeping Assist, Lane Centering, Blind Spot and Active Blind Spot monitoring)
- Low speed maneuvering systems (Parking assistance, Semi and Full Autonomous Parking Systems, Rear and surround viewing systems)
- Driver monitoring systems
- Organization and follow-through
- Excellent ability to work in a team and within a complex organization
- High sense of independence and self-responsibility
- Good knowledge of English language. STELLANTIS conducts business in English, including the release of technical documents and meetings with suppliers and STELLANTIS worldwide organization
Preferred Qualifications:
- Education: Master's degree in Engineering
- Specialized education or research in Optics, RF systems, Electronic Materials, Remote Sensing
- Experience building sensor models
- Experience benchmarking sensors and analyzing data
- Experience working directly with ADAS/AD Sensors, such as Radar, LIDAR, Camera, and Ultrasonics
- Experience in authoring system/component level requirements oriented to supplier selection through tenders / competitive bids
- Experience in System Engineering
- Experience in the development of Driving Assistance and Automated Driving systems, including in-vehicle activities and exposure to test drives / field Operation testing activities
- Knowledge of environmental sensing/machine vision technologies required for ADAS and Automated Driving systems inclusive of most of the following:
- Lane/object detection/classification
- SOCs/antenna design/radomes/detectors/lenses, imager system technologies, image processing and data filtering techniques
- Understanding of sensor fusion techniques
- Knowledge of system requirements engineering required for automated driving inclusive of most of the following:
- EE architecture topologies
- System functional partitioning
- Interfaces
- Failure analysis
- Data collection / re-simulation through HIL / SIL techniques
- Knowledge about the main worldwide reference requirements in term of automotive Active Safety assessments / rating (EuroNCAP, US-NCAP/NHTSA, IIHS)
- Knowledge of tools for vehicle data analysis and logging (Canalyzer, CANAPE, ADTF...etc.)
- Knowledge of localization techniques (SLAM, HD mapping, precision GPS, correction services integration)
- Knowledge of Robotic Operating System (ROS)
Equal Opportunity Employer Minorities/Women/Protected Veterans/Disabled.