<p>Join Teslas service software team, where youll work alongside some of the brightest engineers globally to power critical machine learning models for internal service applications. These applications support Teslas service centers, collision centers, global customer relationship management, and insurance claims. As a Machine Learning Engineer, youll tackle complex, ambiguous challenges, transforming them into end-to-end solutions that drive Teslas mission to accelerate the worlds transition to sustainable energy.</p> <ul> <li>Design, develop, and implement machine learning models for service and customer support environments using techniques like supervised learning, convolutional neural networks, and tools such as PyTorch and Pandas </li><li>Collaborate with vehicle service operations, energy service operations, and customer support teams to address operational challenges </li><li>Take ownership of production models, ensuring robust alerting systems for rapid issue resolution </li><li>Work with diverse, heterogeneous datasets (text, voice, images, tabular data) to build scalable solutions </li><li>Translate ambiguous problem statements into actionable, end-to-end machine learning models </li><li>Follow agile development practices and maintain high standards for clean, modular, and sustainable code </li><li>In-depth expertise in Python for high-performance, data-intensive applications </li><li>Proficiency with at least one modern deep learning framework (e.g., PyTorch, JAX, TensorFlow) </li><li>Specialized knowledge in areas such as large language models, recommender systems, or operations research </li><li>Strong foundational understanding of statistics for model comparison and performance evaluation </li><li>Real-world experience deploying and maintaining production machine learning systems </li><li>Passion for writing clean, modular, and sustainable code to transition research into production </li><li>Degree in Computer Science, Data Science, or equivalent experience </li></ul>