Job Overview
As a Staff Mechanical Product Development Engineer- Integrated Predictive Analysis in the Mechanical Center of Excellence, you will lead advanced mechanical research, design, and validation efforts for cutting-edge interconnect systems used in AI data centers, high-performance computing, and next-generation communication infrastructure.
Your role involves developing novel mechanical structures, executing thermomechanical simulations, validating materials, and collaborating cross-functionally to enhance product performance, reliability, and manufacturability. You will operate with a high degree of autonomy and technical depth to define and drive innovation across mechanical platforms—from early-stage PoCs through NPI handoff.
This role is highly cross-functional, requiring collaboration with electrical, signal integrity, system architecture, manufacturing, and supplier development teams.
BU Overview
Consumer, network, and data center applications change at an exponential pace and the Data & Devices (D&D) business unit at TE Connectivity is at the heart of a continuously expanding connected life. Accordingly, we provide responsive, iterative, and fundamentally agile capabilities and conceive, design, and manufacture to support today's demands. Our customers are building the devices and the infrastructure that is redefining what information technology means. Our products push markets and meet the ever-changing needs of the evolving, more connected, data-driven world. We are enhancing how we do business, focusing on the most important things and staying agile and responsive to the needs of a faster, more connected world.
The Mechanical Center of Excellence (ME COE) plays a critical role in shaping the future of thermomechanical design, reliability engineering, and platform-based product development. By integrating advanced mechanical research, simulation, and manufacturability expertise, ME COE empowers faster, more scalable, and more robust innovation across TE’s high-speed connectivity and AI infrastructure portfolios.
Responsibilities
1. Strategy & Architecture
- Define and drive system-level simulation architecture for integrating design, materials, and manufacturing processes (forming, molding, assembly) into unified digital workflows.
- Influence product and technology roadmaps, embedding integrated predictive simulation, robustness, and digital engineering into next-generation data center, interconnect, and power delivery platforms.
2. Simulation Method Development & Design Enablement
- Develop and deploy integrated predictive engineering methodologies, combining product design, manufacturing simulation, and multiphysics analysis to enable robust, first-time-right solutions for complex electro-mechanical systems (connectors, high-speed I/O, enclosures, power-dense assemblies).
- Drive design optimization and robustness using multi-disciplinary optimization (MDO), design space exploration, sensitivity analysis, and tolerance-aware design.
- Establish predictive design frameworks including reduced-order models (ROMs), compact models, and digital twins linking simulation, test, and field performance.
3. Physics-AI & Workflow Automation
- Drive adoption of Physics-AI approaches combining simulation data, test data, and machine learning to accelerate design cycles and improve predictive accuracy.
- Develop automated simulation workflows integrating CAD, meshing, solving, and post-processing for scalable and repeatable analysis.
- Enable data-driven engineering through pipelines for model calibration, surrogate modeling, and rapid design iteration.
4. Cross-Functional Integration
- Bridge product and process domains ensuring simulation insights translate into actionable design and manufacturing decisions.
5. Validation, Robustness & Governance
- Lead model validation and correlation integrating lab testing with simulation for high-confidence predictions.
- Drive robustness and reliability engineering, incorporating variation-aware design, tolerance stack-up, and failure mode consideration
- Establish best practices and standards for AI agents based on predictive engineering across teams, and product lines.
What your background should look like:
Required Skills/Experience:
- Bachelor’s degree in Mechanical Engineering or Physics with 8+ years of experience, or a Masters degree in Mechanical Engineering or Physics, or equivalent amount of experience in mechanical product development in connector, electronics, or high-reliability hardware industries.
- Hands-on experience in conventional AI/physics AI modeling methods for engineering applications.
- Hands-on experience with CAE process flow automation tools like Optislang, Mode Frontier etc..
- Hands-on experience with mechanical design and modeling using tools such as Creo, SolidWorks, or NX.
- Expertise in simulation tools such as ANSYS, Abaqus, or FloTHERM for thermal/structural analysis.
- Proven experience in DFM, DFA, and transition of mechanical designs to high-volume manufacturing.
- Deep understanding of materials science, including polymers, metals, and thermal materials.
- Experience conducting reliability testing: thermal cycling, vibration, drop/shock, and HALT/HASS.
- Strong problem-solving and analytical skills with a focus on root cause analysis and continuous improvement.
- Excellent communication skills to engage with global engineering, operations, and customer teams.
Nice to have Skills/Experience:
- Experience with micro-mechanics, co-packaged optics, or liquid cooling solutions.
- Familiarity with data analytics, Six Sigma methodologies, or AI-driven simulation optimization.
- Experience working on system-level hardware such as AI servers, switches, or RF modules.
- Patent filings or published research in mechanical design, thermal management, or materials
- Experience managing cross-functional or global engineering projects
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