The Reliability Engineer role focuses on leveraging software and data engineering skills to enhance production reliability in Battery Manufacturing. The position emphasizes the development of intelligent tools and platforms rather than hands-on equipment maintenance. The ideal candidate will bridge reliability engineering principles with modern software development to transform operational data into actionable insights. This role involves collaboration with various teams to drive predictive maintenance and continuous improvement initiatives.

• Degree in Computer Science, Software Engineering, Data Science, or a related Engineering field, or equivalent experience
• 3+ years of experience building software tools, data pipelines, or ML models in a manufacturing, industrial, or operations environment
• Strong programming skills in Python, familiarity with SQL and at least one additional language such as JavaScript/TypeScript, Go, or Java
• Experience with data engineering tools and frameworks such as Apache Airflow, Spark, or dbt
• Proficiency with data visualization and BI platforms like Power BI, Tableau, or Grafana
• Solid understanding of reliability engineering concepts including OEE, MTBF, MTTR, and failure analysis methodologies
• Experience with ML/AI frameworks such as scikit-learn, TensorFlow, or PyTorch
• Familiarity with time-series analysis, anomaly detection, and predictive maintenance modeling
• Experience with cloud platforms like AWS, Azure, or GCP and containerized deployments using Docker or Kubernetes
• Knowledge of Lean Manufacturing, Six Sigma, or Reliability-Centered Maintenance principles
• Experience with version control systems like Git and CI/CD pipelines

• Design and build internal tools, applications, and automation workflows that support predictive maintenance programs
• Create integrations with CMMS, SCADA, IoT, and other data sources to deliver unified dashboards and KPI reporting
• Architect scalable data pipelines that ingest and transform high-volume equipment and production data
• Apply statistical analyses to identify failure patterns and build interactive visualizations that highlight downtime drivers
• Develop and deploy machine learning models for predictive maintenance and anomaly detection
• Build real-time monitoring systems and improve failure classification models for root cause analysis
• Partner with Reliability, Maintenance, Production, and Controls Engineering teams to translate operational challenges into software solutions
• Champion AI-assisted workflows and support Management of Change processes
• Automate manual reliability tasks including spare parts analysis and maintenance planning

• Employees at Tesla are often offered day-one coverage with multiple medical options (some at $0 paycheck cost), dental/vision, company HSA contributions, a 401(k) match, and equity programs. Most roles also include paid time off and holidays, family-building support, employee assistance, commuter and childcare benefits, and access to discounts and wellness programs.