Data Engineer, Machine Learning, Manufacturing Quality

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.

• 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

• 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 withinfrastructure and continuous integration pipelines (e.g. Docker, Kubernetes, Airflow, Jenkins)
• Experience with open source machine learning libraries and frameworks (e.g. Scikit-Learn, Tensorflow, PyTorch, 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

Along with competitive pay, as a full-time Tesla employee, you are eligible for the following benefits at day 1 of hire:

• Medical plans > plan options with $0 payroll deduction
• Family-building, fertility, adoption and surrogacy benefits
• Dental (including orthodontic coverage) and vision plans, both have options with a $0 paycheck contribution
• Company Paid (Health Savings Accounts) HSA Contribution when enrolled in the High-Deductible medical plan with HSA
• Healthcare and Dependent Care Flexible Spending Accounts (FSA)
• 401(k) with employer match, Employee Stock Purchase Plans, and other financial benefits
• Company paid Basic Life, AD&D
• Short-term and long-term disability insurance (90 day waiting period)
• Employee Assistance Program
• Sick and Vacation time (Flex time for salary positions, Accrued hours for Hourly positions), and Paid Holidays
• Back-up childcare and parenting support resources
• Voluntary benefits to include: critical illness, hospital indemnity, accident insurance, theft & legal services, and pet insurance
• Weight Loss and Tobacco Cessation Programs
• Tesla Babies program
• Commuter benefits
• Employee discounts and perks program

Pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The total compensation package for this position may also include other elements dependent on the position offered. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.