ML and Algorithm Engineer

At Aptiv, we are at the forefront of revolutionizing mobility, and we specialize in developing advanced safety systems for the automotive industry, ensuring every aspect of driving is safer and more reliable.

Our department is responsible for the development of radar perception software end-to-end, e.g., processing data received from sensors, generating object data and estimating other important information in the surrounding environment.

Our customers, as well as our internal stakeholders, then use our output to develop feature functions such as Autonomous Emergency Braking (AEB), Adaptive Cruise Control (ACC) and various levels of automated driving functionality.

Your Role:

We are looking for a talented and experienced Machine Learning and Algorithm Engineer for our Radar Perception Division full of ambitious and highly competent developers at our site in Kraków.
In this role, you will actively contribute to the development and advancement of HARP (Hybrid Advanced Radar Perception), a cutting-edge system where radar perception is achieved through a combination of classic algorithms (such as Kalman filters) and state-of-the-art machine learning techniques.
You will be at the forefront of creating innovative solutions that enhance the accuracy, reliability, and performance of radar-based systems.

Area of responsibility:

• Investigate and develop Radar perception with traditional and ML approaches of our market-leading perception software solutions

• Investigation and adaptation of the latest developments in technology and methodology into our solution stack

• Development and integration of algorithms in C and Python

• Developing advanced machine learning algorithms for Radar perception

• Training and testing of deep neural networks and other ML models

• Relevant algorithmic problems include object detection and tracking, classification, segmentation, Kalman filtering

• Quality assurance via design, requirement and comprehensive verification and validation according to Aptiv process and industry standards

• Continuous improvement of supporting factors, e.g., simulation tools and testing environment

• Troubleshooting and issue resolution for ongoing programs and projects

• Interaction with system & testing teams, customers and project management

• Working in an Agile SW development team (SCRUM)
   

Your Background:

• A Master's in Computer Science, Data Science, Machine Learning, Artificial Intelligence, or a related field. Equivalent work experience may be considered

• Experience in Radar prediction algorithm development and/or AI/ML models

• Hands-on experiences with popular deep learning frameworks, e.g., PyTorch and TensorFlow

• Proven records with the design and realization of neural networks

• Good understanding of radar perception software, radar signal processing and/or statistics

• Good experience in C/C programming and/or Python and MATLAB

• Fluent in English written and verbally

• Excellent problem-solving skills and attention to detail

• Strong communication and collaboration abilities

• Ability to work in a fast-paced, agile environment

Nice to have:

• Experience working in ADAS projects, preferably in perception or feature function development

• Experience in automotive standards, e.g., A-Spice and ISO26262

• Experience with version control systems (Git/Gerrit)
   

Your Benefits at Aptiv:

• Private health care (Signal Iduna) and Life insurance for you and your beloved ones

• Well-Being Program that includes regular webinars, workshops, and networking events

• Hybrid work (47 days of remote work per year) and flexible working hours

• Employee Pension Plan paid by the employer (you get 3,5% on each gross salary)

• Access to sports groups and Multisport card

Apply today, and together let’s change tomorrow!
 

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Aptiv is an equal employment opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender identity, sexual orientation, disability status, protected veteran status or any other characteristic protected by law.