AI/ML Engineer for Multidisciplinary Engineering Design-Associate Staff
Tasks
- Apply reinforcement learning for engineering problems
- Build data driven surrogate models
- Conduct model design validation using testing results
- Develop AI ML algorithms for engineering applications
- Develop agentic AI methods
- Develop multidisciplinary simulation and optimization workflows
- Implement physics informed machine learning
- Integrate machine learning into physics based simulation
- Perform fluid structural and thermal simulation analysis
- Present results in technical reports and presentations
Perks/Benefits
- 401k match
- Health, dental & vision plans
- Mentorship programs
- Paid leave
- Pension
- Security clearance support
- Tuition reimbursement
- Work-life balance options
Skills/Tech-stack
Agentic AI | Artificial Intelligence | C++ | Data Driven Surrogate Modeling | Data-driven | Design optimization | Fluid Dynamics | Git | High Performance | High-Performance Computing | MATLAB | Machine Learning | Multidisciplinary Design Optimization | Multidisciplinary design | Performance Computing | Physics-informed machine learning | Python | Reinforcement Learning | Structural analysis | Surrogate modeling | Thermal analysis | Version control
Education
Roles
AI | AI/ML Engineer | Engineer | Learning Engineer | ML Engineer | Machine Learning Engineer
Regions
Countries
States
Cities
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