Aptiv
AI/ML Engineer
- Compensation
- Not disclosed
- Location
- Krakow, Poland
- Work setup
- Hybrid
- Seniority
- Intern
- Employment
- Internship
- Experience
- Not specified
- Category
- Ml / AI
- Posted
Skills
Nice to have
- Experience through internships, thesis work, research projects, open-source contributions, competitions, or personal projects related to AI/ML
- Knowledge of perception, prediction, planning, robotics, or autonomous systems
- Experience with multi-sensor processing (camera, radar, lidar, IMU)
- Familiarity with large language models, vision-language models, or foundation models
- Experience with model optimization, deployment, or efficient inference
- Knowledge of C++ and software engineering best practices
- Exposure to cloud-based or large-scale training environments
- Familiarity with automotive, ADAS, autonomous driving, or robotics applications
- Contributions to scientific publications, patents, open-source projects, or technical competitions
- Experience working with Git, CI/CD, and collaborative development workflows
Full description
Your role
- Work on cutting-edge AI technologies that power future ADAS and automated driving systems
- Apply state-of-the-art machine learning and computer vision techniques to real-world automotive challenges
- Gain hands-on experience with large-scale datasets, modern AI frameworks, and production-oriented development workflows
- Collaborate with experienced researchers and engineers in a highly innovative international environment
- Explore emerging areas such as foundation models, multi-modal learning, behavior prediction, and automated parking
- Develop both research and engineering skills while contributing to products deployed in customer vehicles
Your background
- Master's degree (or close to completion) in Computer Science, Machine Learning, Computer Vision, Robotics, Electrical Engineering, Mathematics, Physics, or a related field
- Strong analytical and problem-solving skills with a solid foundation in mathematics, statistics, and machine learning
- Good understanding of machine learning fundamentals and deep learning concepts
- Academic, internship, research, or project experience in one or more of the following areas:
- Computer vision (detection, segmentation, tracking, 3D perception)
- Deep learning techniques (CNNs, Vision Transformers, foundation models)
- Sequential or temporal modeling and processing
- Representation learning, self-supervised learning, or generative AI
- Multi-modal learning
- Hands-on experience with Python and at least one modern ML framework (preferably PyTorch)
- Experience implementing, training, or evaluating machine learning models through coursework, research projects, internships, or personal projects
- Ability to read and understand scientific literature and translate research ideas into practical implementations
- Good communication skills in English
Exceptional recent graduates with strong academic performance, research experience, internships, or outstanding personal projects are encouraged to apply.
Nice to have
- Experience through internships, thesis work, research projects, open-source contributions, competitions, or personal projects related to AI/ML
- Knowledge of perception, prediction, planning, robotics, or autonomous systems
- Experience with multi-sensor processing (camera, radar, lidar, IMU)
- Familiarity with large language models, vision-language models, or foundation models