AI/ML Expert

We are seeking a highly skilled and motivated AI/ML Researcher to design, develop, and deploy cutting-edge computer vision systems specifically for driver modeling applications. This role is pivotal in enhancing the safety, comfort, and personalization of our next-generation automotive interior monitoring products. The ideal candidate will combine strong research skills with practical engineering experience to translate innovation into production-ready, robust, and reliable driver modeling solutions for the automotive industry. Key Responsibilities: Research & Development for Driver Modeling : Conduct pioneering research to develop novel algorithms and models specifically tailored for critical driver modeling tasks, including: Domain-Aware Representation Learning: Investigate and develop effective methods for extracting robust, semantically meaningful, and interpretable features from multi-modal sensor data. This includes leveraging geometric, behavioral cues, alongside modern representation learning techniques, to capture essential aspects of driver state actions and behavior. Driver State and Behavior Analysis: Advanced detection of driver attributes like Distraction, Drowsiness (including micro-sleeps), Sleep onset, and emotional states. This involves developing sophisticated models to understand and predict complex human behavior, leveraging statistical methods, information theory, and probabilistic approaches. Driver Intent and Activity Recognition : Interpreting driver intent, head pose, gaze tracking, eye- gaze estimation, and recognizing specific activities (e.g., phone usage, eating, interacting with vehicle controls). 3D Interior Scene and Driver Interaction Understanding : Interpreting the driver's environment and their interactions within the vehicle cabin for a holistic understanding. Algorithm Implementation & Optimization for Automotive: Design, train, and optimize deep learning models (e.g., CNNs, Transformers, Recurrent Neural Networks) and advanced traditional computer vision algorithms for core perception tasks central to driver modeling, utilizing multi-modal sensor data commonly found in automotive environments (e.g., RGB, IR, Depth cameras). Focus on computational efficiency and real-time performance suitable for embedded systems. Automotive-Grade Data & Pipelines: Devise comprehensive data collection, annotation, and augmentation strategies specifically for diverse driver populations and real-world driving scenarios. Manage and curate large-scale, high-quality automotive datasets for model training, validation, and benchmarking. Stay abreast of the latest advancements in AI/ML and computer vision research relevant to driver modeling, contributing to the company's IP through patents or publications. Required Qualifications & Skills: Education : Master's or PhD in AI/ML, Computer Science, Electrical Engineering, or a related technical field, or equivalent practical experience with a strong focus on computer vision for automotive applications. Technical Proficiency : Strong programming skills in Python and C++, with experience in optimizing code for performance. ML/CV Expertise : Deep understanding of computer vision fundamentals, image processing, and proven experience with both traditional computer vision techniques (e.g., feature descriptors, geometric vision, optical flow) and machine learning/deep learning frameworks (such as PyTorch and TensorFlow). Ability to intelligently combine these approaches for robust solutions. Hands-on Driver Modeling Experience: Demonstrable hands-on experience building, training, and deploying perception systems specifically for driver modeling, human-centric AI, or related automotive interior sensing applications. This includes academic projects, industry experience, or contributions to open-source initiatives focused on driver understanding. Core Concepts : Solid grasp of mathematical, statistical, and information theory concepts, including linear algebra, calculus, prob