Simulation R&D Engineer

About the role

We are seeking a highly motivated engineer to develop and apply artificial intelligence and machine learning (AI/ML) techniques to accelerate structural and electrical simulations. This role bridges product development, finite element analysis (FEA), signal integrity (SI) analysis, and AI modeling, enabling faster and smarter product design.

Responsibilities

• Develop, implement, and validate next-generation simulation frameworks that leverage data-driven and physics-based approaches to accelerate structural and multi-physics analyses.
• Integrate physics-informed or reduced-order models into existing FEA workflows (e.g., Abaqus, LS-DYNA, ANSYS Workbench) to enhance speed and scalability.
• Build and calibrate surrogate models that accurately approximate high-fidelity simulations while maintaining minimal accuracy loss.
• Automate data generation and management pipelines from FEA results to support model training, validation, and continuous improvement.
• Analyze and balance trade-offs among model fidelity, computational efficiency, and generalization performance for different applications.
• Evaluate and deploy emerging AI-for-simulation technologies (e.g., Altair PhysicsAI, Ansys SimAI) to accelerate structural, thermal, and electrical co-simulation and design optimization.
• Design and enhance automated optimization workflows that couple FEA and signal integrity simulations (e.g., using ModeFrontier, ANSYS OptiSLang, or equivalent platforms).
• Document, publish, and communicate findings to promote adoption of advanced simulation methodologies across engineering teams.

Requirements

• B.S. Degree in Mechanical Engineering, Computer Science, Data Science, or a related field.
• Strong foundation in solid mechanics, finite element methods (FEM), and numerical modeling for structural and multi-physics applications.
• Hands-on experience with one or more major FEA tools (e.g., Abaqus, ANSYS Workbench, LS-DYNA), including setup, analysis, and interpretation of results.
• Proficient in Python programming, with experience in numerical and scientific computing libraries such as NumPy, SciPy, and related tools.
• Experience with data preprocessing, model training, and validation workflows, including handling simulation datasets and building data pipelines for AI/ML applications.
• Excellent communication skills, with the ability to convey complex technical concepts effectively to interdisciplinary teams and stakeholders.

Qualifications

• M.S. or Ph.D. in Mechanical Engineering, Computer Science, Data Science, or a related field, with a strong focus on computational modeling or AI applications.
• Experience with advanced machine learning architectures, such as Physics-Informed Neural Networks (PINNs) etc., for physics-based modeling.
• Prior exposure to AI-driven simulation frameworks such as PhysicsAI, SimAI, or equivalent platforms.
• Background in reduced-order modeling (ROM), surrogate modeling, or Bayesian calibration, with experience in integrating these approaches into simulation workflows.
• Familiarity with CAD/CAE automation and data pipelines for simulation-driven design and optimization.
• Proven ability to translate research concepts into practical, deployable solutions in engineering or simulation contexts.
• Strong record of technical contributions, such as peer-reviewed publications, patents, or conference presentations.

Skills

• Python programming
• Data preprocessing and model training
• Simulation workflows
• Physics-informed neural networks (PINNs)
• Reduced-order modeling (ROM)
• Surrogate modeling
• Bayesian calibration
• CAD/CAE automation
• Data pipelines
• Signal integrity analysis
• Finite element analysis (FEA)
• Automated optimization workflows
• Documentation and communication

Benefits

• Medical
• Dental
• Vision
• Flexible spending and health savings accounts
• Life insurance
• Disability
• Retailer
• Education assistance
• Infertility assistance
• Paid parental leave
• Adoption assistance

Pay

$90,000 - $120,000 per year. This role is eligible for variable pay, issued as a monetary bonus or in another form.

Schedule

N/A