# ADAS Hardware Systems Integration Engineer

**Company**: Ford Motor Company
**Location**: Dearborn, MI
**Work arrangement**: hybrid
**Experience**: senior
**Job type**: full-time
**Salary**: $115,000-$155,000
**Category**: Engineering
**Industry**: Automotive
**Wikidata**: https://www.wikidata.org/wiki/Q44294

**Apply**: https://efds.fa.em5.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1/job/65419?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_67ed4202-f35

## Description

This position is for an ADAS Hardware Systems Integration Engineer, focusing on ensuring the feature delivers customer expectations. You will develop and implement next-generation data acquisition systems for upcoming architectures and vehicles.

The Vehicle and Architecture Engineering Organization is a global team of approximately 4500 employees across 12 locations, including Detroit, Palo Alto, Mexico, Europe, and Asia. The team develops and tests vehicle architectures and advanced features, managing a capital expenditure budget of over $1B.

## Responsibilities

- Lead/support vehicle instrumentation testing and troubleshooting

- Lead/support revisions to vehicle instrumentation design

- Troubleshoot vehicle instrumentation issues related to hardware and software

- Complete vehicle module software and configuration updates

- Identify root causes and resolve vehicle issues to enable ADAS features/functions

- Perform hands-on troubleshooting for Diagnostic Trouble Code (DTC) and configuration issues

- Understand and verify vehicle specifications for feature/system validation

- Understand ADAS test methods and required feature/system behaviors

- Support ADAS feature/system validation testing and development, including vehicle and virtual methods (e.g., VIL and HIL)

- Deliver efficiency improvements in test operations activities via process development, team training, and tools creation

- Develop tools for data collection and analysis using MATLAB, CAN, Python, etc.

- Support and coordinate root-cause analysis with internal functions and external suppliers

## Qualifications

- Bachelor’s Degree in Electrical Engineering, Mechanical Engineering, Computer Science, or related degree

- 3+ years of experience in developing features or systems in the ADAS domain using radars, cameras, or ultrasonic sensors

- Troubleshooting experience with electromechanical systems

- Experience with instrumentation equipment and typical automotive interfaces (CAN, CANFD, Autosar, Auto-Ethernet, etc.)

- Experience using Vector CANape, CANalyzer, and dSPACE Controls Desk or similar tools

- Experience with Matlab/Simulink and virtual validation methods (VIL/HIL/MIL)

- Good communications and project management skills

- Strong oral and written skills

- Ability to work independently and take initiative

- Strong teamwork and interpersonal skills

## Benefits

- Immediate medical, dental, vision, and prescription drug coverage

- Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up child care, and more

- Family building benefits, including adoption and surrogacy expense reimbursement, fertility treatments, and more

- Vehicle discount program for employees and family members, and management leases

- Tuition assistance

- Established and active employee resource groups

- Paid time off for individual and team community service

- A generous schedule of paid holidays

- Paid time off and the option to purchase additional vacation time

## Skills

### Required
- Electrical Engineering
- Mechanical Engineering
- Computer Science
- ADAS
- Radar
- Camera
- Ultrasonic Sensors
- MATLAB
- CAN
- Python
- Vector CANape
- CANalyzer
- dSPACE Controls Desk
- Matlab/Simulink
- Virtual Validation Methods

### Nice to have
- Master’s Degree in Electrical Engineering, Mechanical Engineering, Computer Science or related degree
- Familiarity with actuators and control systems
- Experience applying Systems Engineering principles
- Experience with robotic verification and testing methods
- Experience with differential GPS equipment

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