Systems Integration Engineer
2 days ago
Responsibilities
Lead new product introduction and associated processes for the successful launch of new hardware platforms into our data centers globally. Lead architecture reviews with hardware engineering teams to analyze and develop diagnostic coverage plans for both hardware and software. Lead hardware reviews and drive system Design for Serviceability requirements to ensure form, fit and function for new hardware development in our existing data center environment/architecture. Lead the development and execution of Data Center readiness tooling validation testing based on tooling development plans. Early engagement with design development teams (both internal and external) to drive improvements and influence hardware and tooling architecture. Collaborate with cross functional teams & development partners to deliver aligned new hardware platform roadmaps and gain agreement on implementation milestones. Collaborate with cross functional partners in Meta's Data Center Operations team to understand infrastructure deployment and operational requirements. Collaborate with Production Engineers, Hardware Validation Engineers, Tooling Automation Engineers, and Data Center Operations Engineers to build thorough test strategy and test plans for validating the software needed for Data Center Operations. Work with ODM/OEM vendors as needed to define the product specifications, development plans & test plans. Capturing lessons learned for issues in Production and creating test cases to address those issues in future hardware platforms. Experience triaging, testing, developing, and debugging hardware platforms. Demonstrate technical skills and experience creating documentation for users of all levels.
Qualifications
Requires Master's degree (or foreign equivalent) in Industrial and Systems Engineering, Mechanical Engineering, Optical Engineering, Physics, Electronics, or a related field Requires graduate-level course, research project, or internship involving the following : Modeling and Simulation: Simio and FlexSim, Queueing theory, Discrete event simulation (warehouse optimizations) Lean Six Sigma green belt: lean manufacturing, statistical process control, statistical analysis tools (minitab) Advanced Engineering Analytics: (Data modeling, programming, data visualization, System Architecture and Integration) using Python Electronics Packaging: domain knowledge of semiconductor manufacturing industry at various levels of packaging, theory and applications of surface mount technology and associated abnormalities Business Intelligence Tools: PowerBI and Kibana Computational Tools: practical code-writing for scientific and engineering problems using Mathematica, Julia, and VBA Statistical analysis and methodologies Enterprise Systems Engineering: Lean Manufacturing and Project Management Supply chain network optimization and Inventory Optimization and AI model development for Natural Language Processing
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