[Remote] Staff Mechanical Product Development Engineer- Integrated Predictive Analysis
Note: The job is a remote job and is open to candidates in USA. TE Connectivity is a company focused on creating a safer, sustainable, and more connected world. As a Staff Mechanical Product Development Engineer, you will lead advanced mechanical research, design, and validation efforts for interconnect systems used in AI data centers and high-performance computing, while collaborating cross-functionally to enhance product performance and reliability.
Responsibilities
- 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
- 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
- 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
- Bridge product and process domains ensuring simulation insights translate into actionable design and manufacturing decisions
- 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
Skills
- 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
- 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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