We are seeking a highly skilled Prediction Engineer to join our autonomous driving team. This role combines classical prediction techniques with advanced machine learning approaches to enhance the safety, efficiency, and intelligence of our autonomous vehicle systems. The ideal candidate will have a strong foundation in both classical algorithms and modern machine learning methods, including deep learning.

What you'll be doing:

• Develop and implement hybrid prediction algorithms that integrate classical methods with machine learning models for vehicle behavior and trajectory planning
• Optimize existing algorithms for numerical efficiency and real-time application in autonomous driving scenarios
• Design and implement machine learning models, including classical ML (e.g., decision trees, SVM) and deep learning architectures (e.g., Transformers, CNNs) for various prediction tasks
• Conduct rigorous testing and validation of prediction algorithms against diverse datasets and in simulated environments
• Collaborate with cross-functional teams to integrate prediction models into the overall autonomous driving stack
• Stay current with the latest advancements in AI and machine learning, particularly in the context of autonomous vehicles

• MS or PhD in Computer Science, Engineering, Mathematics, or a related field with a focus on machine learning, AI, or robotics
• Strong programming skills in C++, Python, and experience with machine learning frameworks (e.g., TensorFlow, PyTorch)
• 5+ years of experience in developing and implementing both classical and machine learning-based prediction algorithms
• Solid understanding of classical prediction experiences, numerical optimization techniques, and their application in autonomous systems
• Proven expertise in machine learning, including classical ML algorithms and deep learning architectures
• Experience with data analysis, feature engineering, and model evaluation techniques
• Excellent problem-solving skills and ability to innovate in the field of algorithmic and ML-based prediction
• Strong communication skills and ability to work effectively in a collaborative team environment

• Experience with productization of AI/ML technology, especially in the automotive or robotics industries
• Familiarity with real-time system constraints and the ability to optimize algorithms for computational efficiency
• Knowledge of vehicle dynamics and control systems
• Contributions to open-source projects or publications in relevant peer-reviewed journals or conferences
• Experience with simulation tools and environments for autonomous driving
• Familiarity with sensor fusion techniques and processing of multi-modal data (e.g., LiDAR, camera, radar)