Develop and maintain core libraries and APIs for the HOOPS AI toolkit
Design, implement, and improve machine learning models for industrial 3D use cases
Prepare and curate complex 3D datasets, including CAD, B-Rep, mesh, and point cloud data
Build robust preprocessing pipelines for industrial 3D data, including normalisation, alignment, sampling, and dataset versioning
Run, analyse, and document experiments with clean, reproducible code and reliable evaluation protocols
Collaborate on model training, validation, benchmarking, and regression testing
Package and deploy models into production-grade services and inference pipelines
Improve CI/CD pipelines, automated testing, and release workflows using Azure DevOps and GitHub
Communicate technical designs, results, and progress clearly in English
Exemplify the Core Values of Tech Soft 3D on a consistent basis

Master’s degree in Computer Science, AI/ML, or equivalent relevant experience
3+ years of professional experience in software engineering and applied machine learning
Strong Python skills with a focus on clean architecture, testing, and performance
Experience with modern ML frameworks, ideally PyTorch
Solid foundations in machine learning and computer science principles
Experience with Git, CI/CD pipelines, and modern development workflows
Familiarity with Docker and deploying services through APIs
Excellent collaboration and communication skills
Strong written and oral English language proficiency

Machine Learning Software Engineer

Key skills