Machine Learning Engineer

💻 Job Title: Senior Machine Learning Engineer (Automotive Background)📍 Location: Frankfurt, Germany (Hybrid)💼Employment Type: Full-time 🔍 Job Overview Expert or Senior ML Engineer We are looking for a Senior ML Engineer with deep expertise in spatiotemporal modeling and machine learning to join our autonomous driving team. In this role, you will design, develop, and deploy advanced algorithms that predict the future trajectories of surrounding road users, including vehicles, cyclists, and pedestrians. Your work will directly influence planning and decision-making, enabling safe, efficient, and human-like driving behavior in complex traffic environments. Develop state-of-the-art deep learning models for motion prediction in multi-agent, interactive driving scenarios Design and implement spatiotemporal architectures such as transformers, GNN, RNNs, or diffusion models for trajectory forecasting Fuse multi-modal perception outputs from camera, LiDAR and radar sensors into robust prediction pipelines Build interaction-aware and scene-context models that account for traffic rules and social behaviors Optimize prediction models for real-time performance on automotive embedded platforms Validate and benchmark models against large-scale datasets and diverse simulation scenarios Collaborate closely with perception, mapping, planning, and other teams to ensure seamless integration into the autonomous driving stack Contribute to dataset curation, annotation strategies, and scenario design for motion prediction tasks Requirements Strong foundation in machine learning and deep learning, with emphasis on spatiotemporal modeling and trajectory forecasting Proficiency in Python and/or C++, with experience in ML frameworks such as PyTorch or TensorFlow Hands-on experience with motion prediction models (Transformers, LSTM, GNN etc.) Familiarity with multi-modal sensor fusion and tracking systems Solid understanding of vehicle dynamics, traffic flow modeling, and interaction-aware prediction Experience optimizing and deploying models for real-time inference on embedded systems Strong problem-solving skills, ability to rapidly prototype, and track record of delivering production-quality models Familiarity with planning and control pipelines, and how prediction interfaces with downstream modules Experience with simulation tools Nice to have: Experience in ADAS or autonomous driving motion prediction systems