You will work in an internationally oriented market segment with a broad customer base of OEMs. YOUR QUALIFICATIONS Completed technical degree in computer science/electrical engineering/mechatronics Professional experience in a comparable environment and practical experience in the analysis and specification of system requirements, preferably in the automotive industry using DOORS and RhapsodyProficient use of the SysML modeling language and experience in the development of ASIL C/D systems Systematic, process-oriented approach (SPICE, V-model) and very good technical understanding Experience in the field of digital control engineering and power electronics is desirable Experience with System-FMEA and System-FTA is desirable Excellent communication skills in English Enthusiasm and a desire to further develop oneself and the HV DC/DC and OBC products WHAT WE OFFERMobile Working and flexible working time modelsExtensive career and further training opportunities Sports and health program HELLA in Motion as well as partner of the company fitness network WELLPASSDiscounted Germany ticket for bus and trainFree coffee and water, company restaurants and cafésBicycle leasing and numerous employee benefitsCompany pension plan with HELLA allowanceFamily support: family service and advice on caring for relativesEmployee events Even if you do not meet all our requirements, do not hesitate to apply to us, because the further development of our employees is very important to us and opens up a wide range of opportunities for you in our company.
elasticsearch AWS Python Google BigQuery Google Cloud Platform Numpy Pandas Gitlab What you will do Design and develop innovative algorithms to power a personalized shopping experience, leveraging cutting-edge machine learning techniques Deploy your solutions into production, taking full ownership and ensuring high performance and scalability Combine your data science expertise with a pragmatic, agile approach to find innovative solutions and drive measurable results within a fast-paced environment Challenge the status quo by identifying areas for improvement in existing retrieval and reranking systems, particularly those relying heavily on business logic, and propose data-driven solutions Thrive in a dynamic, fast-paced environment with a flat hierarchy, where your ideas and contributions can make a real difference Who you are Proficiency in Python or experience with at least one scientific computing language (e.g., MATLAB, R, Julia, C++) Strong SQL skills with experience in analytical or transactional database environments Theoretical understanding of machine learning principles, coupled with a hands-on approach to building and iterating on models Proven experience in building and deploying machine learning solutions that deliver tangible business value Strong understanding of data structures, algorithms, and tools for efficiently handling large datasets (e.g. pandas, numpy, dask, arrow, polars, …) Experience designing, building, and managing data pipelines Familiarity with cloud-based model training and serving platforms (e.g., GCP Vertex AI, Amazon SageMaker) Solid understanding of statistical methods for model evaluation Big Data: Experience analyzing large datasets using statistical and machine learning techniques DevOps: Familiarity with CI/CD tools (e.g., GitLab CI/CD, Hashicorp Terraform) is a plus Generative AI: Experience with generative AI and agentic frameworks (e.g., LangChain, ADK, CrewAI, Pydantic AI, …) is a plus Understanding of recommendation, retrieval and reranking systems in e-commerce and retail is a plus Excellent written and verbal communication skills in English Ability to effectively communicate complex machine learning concepts to both technical and non-technical stakeholders Proven ability to collaborate effectively within a team to establish standards and best practices for deploying machine learning models A proactive approach to knowledge sharing and fostering a quick development environment Nice to have Experience with BigQuery Knowledge of time series and (graph) neural network models Familiarity with statistical testing and Gaussian Processes Strong Knowledge of Computer Vision libraries, (e.g. OpenCV, TensorFlow, PyTorch) Experience maintaining Machine Learning pipelines through MLOps frameworks (e.g.