Machine Learning Engineer

• 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.
  

Requirements

• 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
  

Benefits

• 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