Software Engineer, Machine Learning Operations, Manufacturing Quality

What to Expect

The Manufacturing Quality Data Engineering team specializes in predicting safety critical issues before they occur, protecting our customers. 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 data pipelines for global machine learning platforms.

What You’ll Do

• Design and develop anomaly detection platforms for creating, tracking, and applying statistical and machine learning models in production environments, with a focus on identifying deviations in real-time manufacturing processes using high-resolution and time series data from global sites
• Create and refine machine learning models to maximize accuracy and impact, incorporating techniques like sequence modeling (e.g., LSTMs, transformers) and feature engineering; engage stakeholders and rapidly iterate based on feedback to improve predictions for equipment failures and quality issues
• Design and develop ETLs, data pipelines, automation systems, and APIs for retrieving, processing, analyzing, and visualizing batch and real-time data, ensuring scalability and low-latency handling of large-scale datasets from worldwide equipment sources
• Analyze manufacturing, equipment, and vehicle data to extract useful statistics and insights about failures, enabling early prediction of issues and proactive actions through ML-driven forecasting and pattern recognition across global sites
• Engage with cross-functional teams to identify underutilized data sources and invent new ML-based methods to interact with and derive insights from them, such as advanced clustering or predictive analytics for site-specific optimizations

What You’ll Bring

• Bachelor's Degree in Computer Science, Information Technology, or a related field, or equivalent experience
• 3+ years of work experience in data analytics, data engineering, machine learning or related fields
• Extensive experience writing software with Python
• Experience with multiple data architecture paradigms (e.g. MySQL, MicrosoftSQL, Oracle, MongoDB, Kafka, Hadoop, Hbase, Spark)
• Experience with infrastructure and continuous integration pipelines (e.g. Docker, Kubernetes, Airflow, Jenkins)
• Experience with open source machine learning libraries and frameworks (e.g. Scikit-Learn, Tensorflow, Py Torch, Keras) and introduce accurate models to a production environment
• Able to work under pressure while collaborating and managing competing demands with tight deadlines
• A passion for machine learning and a results-oriented mindset