ADAS Planning Algorithm Engineer

Aptiv•Troy, MI

10d•Onsite

About The Position

We are Aptiv - a global technology company with 190,000 specialists in 46 countries. We develop innovative software and build the hardware to bring autonomous driving cars, advanced driver-assistance systems, connected vehicles and smart cities to life in a way that only we can. We work in partnership with almost all car manufacturers. Our sensors, systems and software can already be found in almost all passenger cars today. With our deep domain expertise, Aptiv is developing solutions that solve our customers' toughest challenges. We are enabling the transition to software-defined vehicles supported by electrified and intelligently connected architectures – which will combine to power the future of mobility. This position is part of our Intelligent System: Sensors & Compute. We are currently looking for an ADAS Planning Algorithm Engineer to work in our Troy, MI location. The successful candidate will lead the development, implementation, and validation of advanced behavior and motion planning algorithms for ADAS and automated driving systems. This role involves algorithm design, simulation and vehicle testing, performance analysis, and collaboration across perception, controls, systems, and software engineering teams.

Requirements

Master's degree in Electrical Engineering, Computer Science, Robotics, Mechanical Engineering, or a related technical field.
2+ years of industry experience developing algorithms in MATLAB and/or C/C++.
2+ years of experience in behavior planning, motion planning, trajectory generation, decision making, or autonomous vehicle navigation systems.
Experience developing automotive software or systems for ADAS, automated driving, robotics, automation, or related domains.
Experience throughout the automotive product development lifecycle, from requirements through validation and release.
Proficiency with Git/Gerrit, Jira, Confluence, or similar development and collaboration tools.
Experience with requirements management tools such as Polarion or equivalent.
Strong problem-solving and data analysis skills.

Nice To Haves

Advanced knowledge of behavior planning, motion planning, trajectory optimization, prediction-awareness, and decision-making under uncertainty.
Deep understanding and experience with graph-based planning, optimization-based planning, and MPC.
Experience integrating machine learning based components into autonomous driving stacks.
Experience with sensor fusion outputs and interaction with perception systems.
Experience tuning and validating ADAS features against objective performance metrics.

Responsibilities

Design, develop, and implement advanced behavior and motion planning algorithms for ADAS and automated driving applications.
Develop solutions for complex urban and highway driving scenarios, including interactions with dynamic agents and uncertain environments.
Validate algorithm performance through simulation, SIL/HIL testing, and real-world vehicle evaluation.
Analyze driving data to identify performance gaps, root causes, and improvement opportunities.
Perform in-vehicle testing, debugging, and calibration using rapid-prototyping and data analysis tools.
Optimize algorithms for real-time embedded deployment.
Define, track, and report algorithm performance metrics and KPIs.
Collaborate with perception, controls, systems, software, and product teams throughout the development lifecycle.
Ensure compliance with ASPICE, ISO 26262, and SOTIF processes and requirements.