Zeekr Technology Europe AB

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. At Geely Technology Europe, we are shaping the future of mobility through innovation, collaboration and technology. As our business continues to evolve, compliance plays an increasingly important role in enabling sustainable growth, managing risk and supporting sound decision-making. We are now looking for a Compliance Counsel. In this role, you will take a leading position in developing and strengthening our compliance framework across Sweden and Germany, working closely with stakeholders throughout the organization. This is a broad and hands-on role that spans a broad range of compliance areas, including corporate compliance, ethics, ESG, data governance, cybersecurity, trade compliance and emerging technology regulations. You will work closely with Legal, HR, IT, Finance, Procurement and business teams, you will drive cross-functional initiatives that strengthen governance, reduce risk and promote a culture of integrity throughout the organization. What You'll Do As Compliance Counsel, you will act as a trusted advisor to business leaders and cross-functional teams on compliance and governance matters. You will: * Develop, implement and continuously improve our compliance management framework. * Provide practical guidance on compliance risks, regulatory requirements and ethical business conduct. * Monitor and assess legal and regulatory developments relevant to our business. * Drive compliance initiatives across areas such as ESG, data governance, cybersecurity, trade compliance and emerging technology regulations. * Lead compliance risk assessments and support the implementation of risk mitigation measures. * Develop and maintain policies, procedures and governance documentation. * Deliver compliance training and awareness activities across the organization. * Support investigations, speak-up processes and other integrity-related matters. * Lead third-party due diligence activities and support compliance requirements within procurement and contracting processes. * Drive continuous improvement through monitoring, audits and compliance reviews. Who You Are: We believe you are an experienced compliance professional with a strong legal foundation and a pragmatic, business-oriented mindset. You are comfortable navigating complex regulatory environments while building strong relationships across functions and levels of the organization. To succeed in this role, you bring: * A law degree or equivalent legal qualification. * Strong experience within compliance and legal advisory, including hands-on experience in compliance management, regulatory affairs, risk management and internal controls. * Experience working in multinational organizations and across different jurisdictions. * Proven experience developing, implementing and operating a compliance management system within a multinational business environment. * Strong understanding of corporate governance principles and compliance frameworks. * Broad knowledge of anti-bribery and corruption (ABAC), ESG, sanctions, data governance, NIS2, cybersecurity, trade compliance and related regulatory frameworks, combined with hands-on experience from several of these areas. * Experience advising senior management and presenting complex compliance risks and recommendations in a practical, business-oriented and decision-focused manner. * The ability to independently lead complex compliance matters, exercise sound risk-based judgement and drive cross-functional initiatives involving multiple stakeholders. * Solid experience working with EU compliance matters, preferably including Sweden and/or Germany. * Professional fluency in English. Additional European languages, particularly German, are considered an advantage. Why should you join us? Let's face it, there are plenty of opportunities out there. But here's why joining us is a game-changer: * Culture & Community: We're more than just colleagues, we're a tight-knit community that supports and celebrates each other's successes. * Opportunity for Growth: At Geely Tech Eu, your growth is our priority. We provide ample opportunities for learning, development, and advancement. * Impactful Work: Make a real difference! Join us in tackling exciting challenges and contributing to projects that have a positive impact on our customers and society. * Flexibility & Balance: We understand that life happens, which is why we offer flexibility and work-life balance to ensure you can thrive both personally and professionally. * Perks & Benefits: From competitive salaries to awesome perks like 30 vacation days, 8 additional ATK days and an annual STI program to reward your performance, we've got you covered. Do you want to join us on our journey? Welcome, to contact us for more information: Bo Huo, bo.huo@zeekrtech.eu, Head of Legal & Compliance, for questions regarding the position. Sofie Martinsson, Recruiter, sofie.martinsson@zeekrtech.eu for questions regarding the recruitment process. Last Application date: 2026-11-04 Apply today, we will perform ongoing selection during the application period. We look forward to hearing from you. To ensure a fair and objective recruitment process, we have chosen not to request a personal letter, though you are welcome to include one if you wish. Instead, we rely on selection questions and assessment tests, allowing us to focus on your experience and competence for a more efficient and unbiased recruitment process. A background check will also be conducted on the final candidate, including verification of personal details, employment history, financial standing, and any criminal records. To find out more about Geely Tech EU, visit our website. Read more about our recruitment process here. Please note that due to GDPR, we can only accept applications sent through the recruitment system, not via email or other channels.

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. Project Description:  Vehicle motion and safety functions perform better when they know what road surface the vehicle is on. The road surface can be classified from signals the vehicle already measures, using supervised time-series classification models trained on labeled recorded drives. This thesis builds on a previous master's thesis successfully carried out in our department and extends that work in three directions. First, some road surfaces are rare, hard to reach or costly to collect data on, so data augmentation and generative modeling on existing recordings could add road surface classes for them and improve the data balance. Second, data from several vehicle models on similar road surfaces exists, which opens the possibility of one pre-trained model whose learned representations generalize across vehicle variants despite the domain shift caused by their mechanical architecture. Third, today's models use a fixed input sequence length (context window), while some road surfaces benefit from a longer one, so a context length chosen at inference time could serve each road surface better. Scope The thesis investigates three extensions to road surface classification and evaluates them against the existing approach. * Data analysis and baseline: characterize the class and domain distributions of the available data across road surfaces and vehicle models, and establish a baseline, evaluation metrics and train/validation/test splits. * Synthetic data generation techniques: investigate data augmentation and generative modeling methods, such as GANs and other structured and unstructured style transfer techniques, to produce realistic additional samples from existing recordings, to add road surface classes that are hard to collect data for and improve the data balance, and assess both the fidelity of the generated data and its effect on per-class classification performance. * Towards foundational cross-vehicle generalization: investigate whether a single generalizable road surface classification model can be pre-trained on data from multiple vehicle models, and how well it transfers under domain shift to vehicles with different platforms. * Variable context length: investigate sequence models that accept variable-length input, so the context length can be chosen at inference time, and study the trade-off between context length, classification accuracy and inference latency for different road surfaces. * Real-time feasibility: assess model size, computational cost and inference latency with a view to embedded use. Expected Outcomes The thesis is expected to show how far synthetic data can extend road surface classification to hard-to-collect road surfaces, how well one model generalizes across vehicles, and what a variable context length gains, within real-time limits. Deliverables * A quantified baseline of current road surface classification performance per road surface class and per vehicle model. * A method for generating synthetic road surface data from existing recordings, with an evaluation of its fidelity and its benefit for adding hard-to-collect road surface classes and improving the data balance. * An assessment of the feasibility of a single road surface classification model that generalizes across vehicle models, compared with vehicle-specific models. * An approach for a variable context window whose length is chosen at inference time, with an analysis of the accuracy–latency trade-off. * An evaluation on recorded data and a real-time feasibility assessment of the proposed methods. * A master's thesis report, with the aim of a scientific publication. Your skills and background * Ongoing Master's degree in Data Science, Machine Learning, Complex Adaptive Systems, Vehicle Engineering, Systems and Control, or a related field * Strong background in machine learning and deep learning, including time-series or sequence modeling * Experience with one or more generative modeling, data augmentation, representation or transfer learning, and domain adaptation * Experience with machine learning frameworks (e.g. PyTorch, TensorFlow) * Knowledge in signal processing, vehicle dynamics, control systems or applied physics * Strong programming skills in Python; MATLAB/Simulink and C/C++ * Familiarity with embedded or real-time computing systems * Strong analytical and problem-solving skills ---------------------------------------------------------------------------------------------------------------------------------- Why you should join Geely Tech Eu We are engineers, developers, and innovators from around the world. Joined together by entrepreneurship, our unique blend of global culture, and a belief in a smarter more sustainable future. At Geely Tech Eu we fast-track innovation and transform ideas into pioneering technology solutions, doing your master thesis here is no different. We are convinced that a thesis project is a major contribution to our innovation capabilities and long-term development. You'll have a great opportunity to use your skills and creativity to push the boundaries of what´s possible. What happens when you apply If this sounds interesting and you match the requirements, please don't hesitate to submit your application with a CV and cover letter. Shortlisted candidates will be contacted for an interview to further discuss the project's details and expectations.  This thesis project is intended for 1-2 students. Applicants may name a preferred partner in their cover letter and must attach a university transcript. ---------------------------------------------------------------------------------------------------------------------------------- Supervisor: Karthik Prasad, Expert Motion Systems, karthik.prasad@zeekrtech.eu, please contact for more information about the project Starting date: January 2027 Last application date: 2026-10-31 Apply today. We will perform ongoing selection during the application period. 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.

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. Project Description:  Automated driving and driver-assistance functions need to know how much performance the vehicle has left in each situation, its capability envelope. Planning and control algorithms usually rely on simplified models and fixed limits, which can be either too optimistic or too conservative. High-fidelity, physics-based simulation and reachability analysis capture these limits accurately but are far too computationally expensive to run on board. This is an open problem at the intersection of machine learning, simulation and control, how to learn fast and reliable models from expensive simulations, quantify their uncertainty, and adapt them to real-world data. Scope: The thesis takes the vehicle's performance limits from high-fidelity simulation to a real-time, self-adapting, data-driven model ready for assisted and automated-driving functions. * Feature and sensitivity analysis: identify which vehicle, road and actuator variables drive the limits. * Simulation-based data generation: design efficient sampling strategies, such as design of experiments or active learning, to build training data from high-fidelity models. * Machine Learning-based modelling and uncertainty quantification: learn fast data-driven models of the limits and quantify how confident they are. * Online learning and adaptation: update the model from real vehicle data so it tracks changes over time and bridges the sim-to-real gap. * Safe, real-time deployment: conservative predictions, out-of-distribution detection and embedded implementation. * Integration and validation: validating the prediction as part of a use case in a simulation environment and/or on the vehicle. Expected Outcomes The thesis is expected to demonstrate that a high-fidelity capability envelope can be made deployable, adaptive and useful for assisted and automated-driving functions, with following deliverables * A quantified comparison between conventional vehicle limits and a high-fidelity capability envelope. * A method for turning high-fidelity envelopes into a real-time, uncertainty-aware prediction. * An approach for adapting the envelope online so it stays consistent with the real vehicle. * A verified and validated prototype, with results from simulation and, where possible, vehicle tests. * A master's thesis report, with the aim of a scientific publication. Your skills and background * Ongoing Master’s degree in Data Science, Machine Learning, Complex Adaptive Systems, Vehicle Engineering, Systems and Control, or a related field * Strong background in machine learning, including Probabilistic or Bayesian methods and uncertainty quantification * Experience with machine learning for time series, dynamical systems or surrogate modelling * Experience with machine learning frameworks (e.g. PyTorch, TensorFlow,.) * Knowledge in control systems, optimization, vehicle dynamics or applied physics * Strong programming skills in Python, MATLAB/Simulink and C/C++ * Familiarity with embedded or real-time computing systems * Familiarity with vehicle simulation tools (e.g. CarMaker) * Strong analytical and problem-solving skills ---------------------------------------------------------------------------------------------------------------------------------- Why you should join Geely Tech Eu We are engineers, developers, and innovators from around the world. Joined together by entrepreneurship, our unique blend of global culture, and a belief in a smarter more sustainable future. At Geely Tech Eu we fast-track innovation and transform ideas into pioneering technology solutions, doing your master thesis here is no different. We are convinced that a thesis project is a major contribution to our innovation capabilities and long-term development. You'll have a great opportunity to use your skills and creativity to push the boundaries of what´s possible. What happens when you apply If this sounds interesting and you match the requirements, please don't hesitate to submit your application with a CV and cover letter. Shortlisted candidates will be contacted for an interview to further discuss the project's details and expectations.  This thesis project is intended for 2 students. Applicants may specify preferred partner in their cover letter. ---------------------------------------------------------------------------------------------------------------------------------- Supervisor: Karthik Prasad, Expert Motion Systems, karthik.prasad@zeekrtech.eu, please contact for more information about the project Starting date: January 2027 Last application date:2027-10-31 Apply today. We will perform ongoing selection during the application period. 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.