Summer Internship Machine Learning For Vehicle Dynamics

We are Geely Technology Europe. A unified European R&D centre within Geely Auto Group, where world-class engineers, developers and innovators push the boundaries of intelligent mobility. Our mission is to shape the next generation of vehicle architectures, digital technologies and intelligent systems for global markets. We integrate European customer and regulatory requirements early in the development process and support multiple brands within the Geely portfolio, including Zeekr, Lynk & Co and Geely. With nearly two decades of engineering experience in Europe, we continue to build smart, sustainable and user‑centric mobility solutions.

We are seeking motivated summer interns to join our Advanced Motion Systems team and contribute to the development of next‑generation, data‑driven motion control functionalities. This includes working with state‑of‑the‑art approaches such as Physics‑Informed Neural Networks (PINNs), adversarial training, and generative methods.

Selected interns will gain hands‑on experience across the entire machine learning lifecycle, including data collection, dataset preparation, model training, evaluation, and deployment. All work will be carried out with careful consideration of real‑world constraints inherent to vehicle platforms and embedded systems.

This position is well-suited for students who are eager to apply their machine learning expertise to engineering domains such as vehicle dynamics and control systems.

What You Will Work On

• You will develop machine learning solutions for vehicle dynamics, including:

• Planning and collecting vehicle sensor data as needed.

• Building pipelines for cleaning, synchronizing, feature creation, labeling, and quality checks.

• Organizing datasets for training and validation, and documenting assumptions.

• Developing and training sequence models for vehicle estimation and prediction.

• Implementing pipelines, tracking experiments, and setting baselines.

• Optimizing models for robustness across varied conditions.

• Defining relevant metrics and validation methods.

• Performing error analysis and stress testing.

• Comparing model approaches with clear recommendations.

• Converting and optimizing models for embedded use, considering technical constraints.

• Validating models on hardware and test scenarios.

• Producing a prototype and documenting the workflow.

• Summarizing findings in reports and presenting results to the team.

Required Skills & Competence

We are looking for students with strong fundamentals in machine learning and practical project experience.

• Currently enrolled or recently completed MSc (or equivalent) program such as Engineering Mathematics, Applied Physics, Complex Adaptive Systems, System Controls & Mechatronics, or a similar engineering discipline.

• Completion of at least 3–4 master’s level courses in Machine Learning, which may include topics such as ML fundamentals, Deep learning, Statistical Learning, etc.

• Strong programming skills in Python.

• Hands-on experience with deep learning frameworks such as PyTorch and/or TensorFlow.

• Experience working with time-series data, including preprocessing, feature engineering, and evaluation.

• Solid understanding of machine learning training and evaluation practices, including train/validation/test splits, metrics, overfitting control, and reproducibility.

• Interest or experience in control systems and/or vehicle dynamics, including areas such as modeling, state estimation, stability and handling concepts, observers and Kalman filtering, and signal processing.

• Strong analytical thinking and problem-solving abilities.

• Ability to communicate clearly and document work professionally.

• Comfortable working in an engineering team environment.

Please provide full transcripts along with your CV in your application

What You Gain

• End-to-end experience in building machine learning solutions for real automotive embedded systems.

• Exposure to practical constraints, including data quality, generalization, latency and compute limitations, and deployment trade-offs.

• Mentorship from engineers working at the intersection of vehicle dynamics, controls, and machine learning.

Internship Information

• Location: Gothenburg, Sweden. No relocation support is offered.

• Salary: Paid at a fixed hourly rate.

• Duration: You need to be available for a full-time internship. The period for the summer internship is between 1 June – 31 August. The start and end date are to be discussed with the recruiting manager.

• Requirements: You need to have a legal permit to live and work in Sweden.

For more information or questions please contact:
Supervisor: Karthik Prasad, Expert Motion Systems, karthik.prasad@zeekrtech.eu

Last application date: 2026-05-29

We look forward to hearing from you! Please note that due to GDPR regulations we can only accept applications sent through the recruitment system, not via email or other channels.