Chennai, Tamil Nadu, India
Information Technology
Full-Time
CADFEM SEA Pte. Ltd.
Overview
Job Description
- Design and develop machine learning models tailored to mechanical engineering challenges, including predictive modelling, simulation optimisation, and failure analysis.
- Utilise deep learning and other advanced ML techniques to improve the accuracy and efficiency of CAE simulations.
- Preprocess and analyse large datasets from CAE simulations, experimental tests, and manufacturing processes for modelling.
- Train, validate, and fine-tune machine learning models using real-world engineering data.
- Optimise models for performance, scalability, and robustness in production environments.
- Collaborate with CAE engineers to integrate ML models into existing simulation workflows (e.g., FEA, CFD, structural analysis).
- Automate repetitive simulation tasks and enable predictive analytics for design optimisation.
- Work closely with mechanical engineers, data scientists, and software developers to identify business challenges and develop data-driven solutions.
- Deploy machine learning models into production environments and monitor their performance.
- Maintain and update models to ensure reliability and continuous improvement.
- Stay abreast of the latest advancements in machine learning, AI, and CAE technologies.
- Apply innovative approaches to solve complex engineering problems.
- Bachelor’s or Master’s degree in Mechanical Engineering, Computer Science, or a related field
- Proven 2-3 years of experience in developing and deploying machine learning models, preferably in mechanical engineering or CAE domain
- Hands-on experience with CAE tools such as ANSYS, Abaqus, or similar FEA/CFD software
- Strong programming skills in Python, R, or Java
- Proficiency in machine learning frameworks (TensorFlow, PyTorch, scikit-learn)
- Experience with data preprocessing, feature engineering, and statistical analysis
- Solid understanding of mathematics, statistics, and problem-solving skills
- Excellent analytical thinking and ability to tackle complex engineering challenges
- Strong communication and teamwork skills to collaborate across disciplines
- Preferred: Experience with physics-informed machine learning and digital twin technologies
- Preferred: Familiarity with automation of CAE workflows and predictive modelling for product design
- Challenging job and a chance to team up with a young and dynamic professional group
- Chance to build yourself as WE grow.
- Remuneration that stays competitive and attractive to retain the best.
- Opportunity to join an organization experiencing year on year growth
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