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Flexcompute

Cloud CAE for fluid, thermal, EM

Physics AI - Thermal-Mechanical Reliability

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeWatertown, NY, USAIn-person

About the Job

Requirements

  • A PhD in Mechanical Engineering, Materials Science, Physics, or a related field, with deep specialization in computational multi-physics.
  • Recognized expertise in 3D-IC reliability, including profound understanding of warpage mechanics, interfacial delamination, and thermal-mechanical coupling in heterogeneous integration.
  • A strong perspective on GPU acceleration and Machine Learning in scientific computing.
  • At least 10 years of experience in the semiconductor or microelectronics industry, including leadership of technical projects that directly impacted product reliability or time-to-market.

Responsibilities

  • Own the technical roadmap for the thermal-mechanical domain and define how Physics AI accelerates traditional finite element analysis and multi-physics workflows to provide real-time reliability insights.
  • Design end-to-end simulation workflows addressing 3D-IC challenges, including through-silicon via stress, micro-bump reliability, and global package warpage.
  • Act as the lead technical partner for semiconductor companies, demonstrating how Flexcompute's speed can transform iterative design cycles from days to minutes.
  • Influence the development of GPU-accelerated solvers and ensure they are optimized for the non-linear material behaviors and multi-scale meshes required for advanced packaging.
  • Recruit, mentor, and lead a high-performing team of engineers specializing in computational mechanics and AI-driven physics.

About the Company

Flexcompute

Cloud CAE for fluid, thermal, EM

Flexcompute offers cloud-based CAE (computer-aided engineering) software that provides proprietary tools for simulating fluid dynamics, thermal analysis, and electromagnetic physics. The platform is delivered as a service, letting engineers run complex simulations in the cloud without needing powerful local hardware, thereby speeding up product design and reducing development costs and risks. Its software-hardware co-design approach enhances the speed and accuracy of simulations, helping manufacturers, semiconductors, and other industries optimize designs efficiently. The company differentiates itself by combining multi-physics simulation capabilities with scalable cloud resources and a focus on making advanced computational analysis accessible to engineers and designers. The goal is to accelerate R&D cycles and enable more reliable, cost-effective hardware development.

Company size
51-200
Company stage
Late Stage VC
Total funding
$82M
Headquarters
Watertown, MA
Founded
2016

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