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Autonomous Driving Software Engineer Jobs in Michigan

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Autonomous Driving Software Engineer information

What does an autonomous driving software engineer do?

An Autonomous Driving Software Engineer designs, develops, and tests software systems that enable vehicles to drive themselves safely and efficiently. They work on algorithms for perception, sensor fusion, planning, control, and decision-making, ensuring vehicles can interpret their environment and make real-time driving decisions. These engineers collaborate with hardware teams, use machine learning techniques, and rigorously test their code in simulations and real-world scenarios to meet safety standards.

What are the key skills and qualifications needed to thrive as an autonomous driving software engineer?

To thrive as an Autonomous Driving Software Engineer, you need strong proficiency in C++ and Python, a solid understanding of robotics, computer vision, and machine learning, and typically a degree in computer science, robotics, or a related field. Experience with ROS (Robot Operating System), simulation tools like CARLA, and familiarity with automotive safety standards such as ISO 26262 are highly valued. Problem-solving ability, teamwork, and effective communication are crucial soft skills in this position. These competencies ensure the development of safe, reliable, and innovative autonomous driving systems in a collaborative and high-stakes environment.

How does an autonomous driving software engineer typically collaborate with hardware and testing teams during a project?

As an Autonomous Driving Software Engineer, you will work closely with hardware engineers and testing teams to ensure seamless integration between software algorithms and physical vehicle components. Regular joint meetings and iterative testing sessions are common, where you’ll align on sensor requirements, data collection, and address real-world performance issues. Effective communication and a collaborative mindset are key, as you’ll often troubleshoot issues that cross the boundaries between software logic and hardware behavior. This multidisciplinary interaction not only enhances your technical skills but also provides valuable exposure to the broader autonomous vehicle development process.

What is the difference between Autonomous Driving Software Engineer vs Vehicle Software Engineer?

AspectAutonomous Driving Software EngineerVehicle Software Engineer
Required CredentialsBachelor's/Master's in Computer Science, Robotics, or Electrical Engineering; experience with AI, perception, and sensor integrationBachelor's/Master's in Software Engineering or related; focus on embedded systems and vehicle control software
Work EnvironmentResearch labs, automotive companies, tech firms developing autonomous systemsAutomotive manufacturing plants, OEMs, suppliers working on vehicle control systems
Industry UsagePrimarily in autonomous vehicle development and testingIn traditional vehicle control, infotainment, and embedded systems

Autonomous Driving Software Engineers focus on developing software for self-driving systems, including perception, decision-making, and sensor integration. Vehicle Software Engineers work on broader vehicle control systems, including embedded software for engine management, infotainment, and safety features. While both roles require strong software skills, Autonomous Driving Software Engineers specialize in AI and sensor data processing, whereas Vehicle Software Engineers focus on embedded systems within vehicles.

How much do autonomous driving software engineers make?

Autonomous driving software engineers typically earn between $100,000 and $160,000 annually, depending on experience, location, and company size. Senior engineers with specialized skills in machine learning, sensor integration, and real-time systems can earn higher salaries, often exceeding $180,000.

How to become an autonomous driving software engineer?

To become an autonomous driving software engineer, you typically need a bachelor's or master's degree in computer science, robotics, or electrical engineering. Strong programming skills in languages like C++ and Python, experience with sensor integration, machine learning, and familiarity with tools such as ROS are essential. Gaining hands-on experience through internships, projects, or research in autonomous systems can also improve job prospects.

What cities in Michigan are hiring for Autonomous Driving Software Engineer jobs?

Cities in Michigan with the most Autonomous Driving Software Engineer job openings:

Infographic showing various Autonomous Driving Software Engineer job openings in Michigan as of August 2026, with employment types broken down into 71% Full Time, 25% Part Time, 1% Temporary, and 3% Contract. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution.

Sr. Vehicle Application Software Engineer

Farmington Hills, MI • On-site

Compal
See more jobs at Compalexternal

Full-time

Posted 21 days ago

Job description

Position Overview

SYLUX is seeking a highly motivated Senior Vehicle Application Software Engineer to join our team in Farmington Hills, Michigan. This position will focus on the development, integration, and validation of advanced software features for SYLUX automotive infrared perception and safety systems.

The Vehicle Application Software Engineer will bridge software development, vehicle integration, ADAS feature development, and real-world validation. The role will transform SYLUX infrared camera and CDAT AI perception capabilities into functional vehicle features, including Automatic Emergency Braking (AEB), Forward Collision Warning (FCW), Rear AEB, Safe Door Opening, Adaptive Cruise Control, and other next-generation safety applications. This is a hands-on engineering position that requires software development and direct interaction with vehicles, sensors, CAN networks, test equipment, and demonstration platforms.

Key Responsibilities

Software Development

Design, develop, integrate, and validate software features utilizing SYLUX infrared cameras and CDAT AI perception software.

Develop, maintain and optimize a globally shared vehicle application used across the engineering teams.

Translate system and customer requirements into functional software features and vehicle-level behaviors.

Support feature development from proof-of-concept to customer-ready vehicle demonstration, validation, and customer evaluation.

Develop algorithms that convert perception output (object classification, distance, tracking, vehicle speed) into vehicle warnings, decisions, and control actions.

Perform driver and kernel-level hardware bring-up, diagnosing and resolving low-level driver and kernel module installation issues.

Extend perception-based feature logic to support new and evolving ADAS applications, including:

o Forward Collision Warning (FCW)

o Automatic Emergency Braking (AEB)

o Rear Automatic Braking (RAB)

o Safe Door Opening (SDO)

o Blind Spot Monitoring (BSM)

o Adaptive Cruise Control (ACC)

o Parking and Low-Speed Safety Features

o Additional infrared-enabled ADAS and automated driving applications


Qualifications

Bachelor's degree in Computer Science, Software Engineering, Electrical Engineering, Computer Engineering, Robotics, Mechatronics, or a related technical discipline.

5+ years of software development experience, preferably within automotive, ADAS, robotics, autonomous driving, embedded systems, or perception technologies.

Experience with automotive infrared, camera, radar, LiDAR, or other perception sensors.

Experience developing real-time or multi-threaded software applications.

Experience with automotive vehicle networks, CAN bus interfacing tools (CANalyzer / kvaser)

Experience with DBC database structures and CAN signal encoding/decoding.

Familiarity with ROS2 framework

Experience with low-level hardware interfaces RS232, SPI, GPIO, Ethernet/UDP, and USB.

Experience working in Linux or NVIDIA development environments.

Experience with Git or similar version-control systems.

Strong programming skills in Python and/or C++.

Ability to produce clear technical documentation, such as system / vehicle architecture diagrams.

Strong written and verbal communication skills.

Ability to work effectively with multidisciplinary and international engineering teams.


Travel

Approximately 15-25% travel, including customer demonstrations, vehicle testing, proving-ground activities, data collection, trade shows, and support of SYLUX programs in the United States and internationally.



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