Sr. Software Engineer, Manufacturing Quality

As part of Tesla's Vehicle Engineering organization, you'll have access to the data gold mine of design, manufacturing, and vehicle data sources, enabling you to design, develop, and deploy innovative generative AI and machine learning platforms globally. In this role, you'll focus on developing the backend of our generative AI systems, including agentic data pipelines and integrations.What You'll DoDesign and deploy scalable architecture for AI applications, including generative systems, using LangGraph and ensuring seamless integration of components to improve overall system performanceDevelop and refine AI and machine learning models, including graph-based models, using technologies like Large Language Model, Retrieval Augmented Generation, TensorFlow, PyTorch, and scikit learn to create intelligent systems that drive business valueCreate and iterate on a comprehensive evaluation framework for generative models, focusing on performance improvements and optimizationArchitect and implement data pipelines and automation systems to streamline data retrieval, processing, analysis, and visualization, ensuring efficient handling of batch and real time dataDesign and implement robust data storage and management systems, leveraging relational databases, NoSQL databases, and graph databases to support diverse data needsExtract actionable insights from manufacturing, equipment, and vehicle data to predict and prevent failures, informing proactive maintenance and quality control strategiesDevelop and integrate back-end APIs, iterating on payload and response designs to ensure seamless interaction with systems and applications, and optimizing overall system interoperabilityWhat You'll BringBachelor's Degree in Computer Science, Information Technology, or a related field, or equivalent experience3+ years of work experience in software developmentExperience with software engineering technologies, including Python, Docker, Kubernetes, MySQL, Microsoft SQL, MongoDB, Elasticsearch, Apache Kafka, and ETLsExperience with machine learning frameworks and technologies, including Large Language Model, Retrieval Augmented Generation, LangGraph, TensorFlow, PyTorch, scikit learn,...