Reliability Engineer, Battery Module

Tesla Motors
Storey County, NV, United States
28 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Working hours
Regular working hours

Tech stack

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
+31 more
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

Job 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

Requirements

  • 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

Benefits & conditions

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

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