FEA Engineer / Software Engineer / Machine Learning Engineer
Description :
We are seeking a skilled engineer to support product design and FEA development.
The ideal candidate will have a strong understanding of both FEA and modern deep learning techniques, hands-on experience in designing and training Client models, and a proven record of deploying models in relevant applications such as computer vision.
The role will involve FEA data processing, organizing datasets, managing the lifecycle of Client models, documenting details, and communicating with cross-functional teams.
Job Responsibility :
- Develop data pipelines from simulation results to Client datasets
- Deploy Client models into production environment ensuring seamless integration with existing codebase.
- Experiment with new algorithms and tools to enhance model performance.
- Create detailed documentation of data processing, model architecture, and training / test results.
- Provide regular updates and reports.
Education :
- Bachelor’s degree in Computer Science, Data Science, Mechanical Engineering, or a related field.
- Master’s degree or higher are preferred. A Ph.D. is a strong plus.
Required Skills :
- Proficiency in Python
- Strong experience in Client frameworks and libraries such as PyTorch or TensorFlow.
- Knowledge of FEA, including element technologies and material models.
- Solid understanding of deep learning architectures such as CNN, RNN, and transformers.
- Hands-on experience with large-scale data processing and analysis.
Preferred Skills :
- Experience in a specific Client application such as computer vision.
- Experience with FEA software (e.g., Abaqus) and scripting.
- Experience with cloud platforms (e.g., AWS, Google Cloud) for training and deployment.
- Familiarity with code collaboration and version control systems (e.g., Git).
As an equal opportunity employer, ICONMA provides an employment environment that supports and encourages the abilities of all persons without regard to race, color, religion, gender, sexual orientation, gender identity or express, ethnicity, national origin, age, disability status, political affiliation, genetics, marital status, protected veteran status, or any other characteristic protected by federal, state, or local laws.
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