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# Reliability Engineer, Battery Module

- **Company:** Tesla Motors
- **Location:** Storey County, NV, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), JavaScript (Programming Language), Artificial Intelligence, Airflow, Amazon Web Services, Data Analysis, Microsoft Azure, Computerized Maintenance Management Systems, Computer Programming, Corona (Software Development Kit), Information Engineering, Data Visualization, Supervisory Control and Data Acquisition (SCADA), Python (Programming Language), Machine Learning, Operational Data Store, Operational Databases, Reliability Engineering, Power BI, Software Tools, Tensorflow, SAP Plant Maintenance, Software Engineering, Software Systems, SQL Databases, Tableau (Software), TypeScript, Pytorch, Grafana, Apache Spark, Mttr, Git, Build Management, Containerization, Scikit Learn, Kubernetes, Information Technology, Data Analytics, Machine Learning Operations, Software Version Control, Data Pipelines, Docker, Golang
- **Published:** July 15, 2026
- **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/17568345?backUrl=%2Fcareer%2F17568345%2FReliability-Engineer-Battery-Module-Nevada-Sparks

## About the Role

* 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 (primary); familiarity with SQL and at least one additional language (e.g., JavaScript/TypeScript, Go, Java)
 * Experience with data engineering tools and frameworks (e.g., Apache Airflow, Spark, dbt, or equivalent). Proficiency with data visualization and BI platforms (Power BI, Tableau, Grafana, or custom-built dashboards)
 * Solid understanding of reliability engineering concepts: OEE, MTBF, MTTR, RCM, preventive/predictive maintenance strategies, and failure analysis methodologies
 * Experience with ML/AI frameworks (scikit-learn, TensorFlow, PyTorch) and deploying models to production
 * Familiarity with time-series analysis, anomaly detection, and predictive maintenance modeling
 * Experience with cloud platforms (AWS, Azure, or GCP) and containerized deployments (Docker, Kubernetes). Exposure to CMMS platforms (SAP PM, Maximo, Fiix) and industrial IoT/SCADA systems
 * Knowledge of Lean Manufacturing, Six Sigma, or Reliability-Centered Maintenance (RCM) principles
 * Experience with version control (Git), CI/CD pipelines, and software development best practices

## Description

We are seeking a Reliability Engineer with strong software and data engineering skills to design, build, and deploy intelligent tools and platforms that optimize production reliability in Battery Manufacturing. Rather than hands-on equipment maintenance, this role focuses on creating software systems, data pipelines, and AI/ML models that enable reliability teams to minimize downtime, predict failures, and drive continuous improvement at scale. The ideal candidate bridges the gap between reliability engineering principles and modern software development to turn operational data into actionable intelligence.
What You'll Do

 * Develop Reliability Software & Platforms: Design and build internal tools, applications, and automation workflows that support predictive maintenance programs, while creating integrations with CMMS, SCADA, IoT, and other data sources to deliver unified dashboards and KPI reporting for OEE, MTBF, and MTTR
 * Engineer Data Pipelines & Analytics: Architect scalable data pipelines that ingest and transform high-volume equipment and production data, then apply statistical analyses such as Weibull and fault tree methods to identify failure patterns and build interactive visualizations that highlight downtime drivers and bottlenecks
 * Implement AI/ML for Predictive Reliability: Develop and deploy machine learning models for predictive maintenance, anomaly detection, and remaining useful life estimation, while building real-time monitoring systems and iteratively improving failure classification models to accelerate root cause analysis and data-driven corrective actions
 * Drive Cross-Functional Collaboration & Automation: Partner with Reliability, Maintenance, Production, and Controls Engineering teams to translate operational challenges into software solutions, champion AI-assisted workflows, support Management of Change processes, and automate manual reliability tasks including spare parts analysis, work order triage, and maintenance planning


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