DSBJ is a leading worldwide technology partner providing critical components for IoT intelligence, with a special focus on Telecommunication Equipment and Metal Precision, LED technologies and Interconnect solutions. Technological innovation is in the DNA of entire organization and is also the cornerstone of DSBJ's success. With cutting-edge production facilities and advanced technology, we constantly deliver state-of-the-art products and quality services. Towards this, DSBJ has established the AI COE team to fully incorporate Big data and Artificial Intelligence into strategic roadmap and enable digital transformation and smart manufacturing/engineering initiatives.
As the Senior / Principal Data Scientist specializing in Smart Engineering, she/he will apply advanced analytics-including machine learning, generative AI, and optimization-within engineering and design domains to convert complex engineering data into actionable insights that drive faster, higher-quality decisions. This role will design, build, validate, and deploy analytical prototypes, taking solutions from concept through production. Working closely with experts in big data, software engineering, and advanced analytics, she/he will also contribute to the development of scalable, cutting-edge analytics capabilities that support evolving business requirements and product innovation.
Main Responsibilities:
- Design and develop algorithms to parse, interpret, and analyse engineering data, inclusive of structured data, technical PDF, 2D drawing, 3D CAD models
- Apply machine learning, deep learning, and geometric modelling algorithms to engineering problems, including drawing understanding (symbol, dimension, feature recognition), CAD feature classification and semantic labelling, part similarity, clustering, and reuse detection
- Collaborate with software and data engineers to productionize models and deploy them as services or internal platforms
- Work closely with mechanical engineers, manufacturing engineers, and process design engineers to translate domain knowledge into AI features
- Communicate advanced analytics solutions to non-technical stakeholders, translating technical insights into clear business value to drive understanding and adoption
- Advise management and stakeholders on best practices for applying advanced analytics to engineering problems through exploration, benchmarking, and evidence-based evaluation
- Work with project manager to break down overall work into manageable and tractable tasks while satisfying time, cost and resource constraints.
- Perform progress check, solution review and documentation on regular basis.
Job Requirements:
- At least Bachelor degree in Mechanical Engineering, Data Science, Applied Mathematics, Statistics, Computing Science. A post-graduate degree is an advantage
- Minimum of 5 years of work experience in academic or business context to apply Data Science, Machine learning, Deep Learning, Optimization to engineering problem
- Profound knowledge (e.g. application, limitation, challenges) of advanced analytics (e.g. rule-based, deep learning, LLM) in analysing the engineering data (e.g. PDF, DXF, STEP, ODB++)
- Hands-on modelling/coding experience using various tools/libraries (e.g. AutoGluon, Ultralytics, Gurobi, TensorFlow, PyTorch, SciKit-Learn, Open CASCADE)
- Proficiency in programming language (e.g. Python, Java) and database querying (e.g. SQL)
- Self-motivated, proactive, independent learner who is willing to learn, experiment, and share knowledge with broader AI COE team to build innovative culture.
- Proficiency in both English and Chinese, to liaise with the Chinese-speaking associates in China Headquarter office.
- Domain knowledge in engineering design, industrial automation and engineering software is highly valued
- Experience in feature recognition, design intent extraction, or DFM/DFA automation is highly valued
