Total 4 job vacancies by Dsbj Pte. Ltd.

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

The Executive Support Manager provides high‑level executive support to senior management, ensuring the efficient coordination of executive schedules, communications, travel, and confidential matters. The role requires strong organisational skills, discretion, and the ability to work closely with internal and external stakeholders to support business operations and leadership effectiveness.

Key Responsibilities

• Manage complex executive calendars, appointments, and schedules, ensuring alignment with business priorities
• Coordinate meetings, prepare agendas, briefing materials, and follow‑up action items
• Handle confidential and sensitive information with the highest level of professionalism and discretion
• Act as a key point of coordination between senior management and internal departments, partners, and external stakeholders
• Support communication flow and follow‑ups on executive decisions and instructions
• Assist with coordination across regional offices or group entities when required
• Oversee executive travel planning, including itineraries, accommodation, and logistical arrangements
• Support executive travel risk arrangements by coordinating with relevant internal teams or external service providers
• Ensure all travel arrangements comply with company policies and local regulations
• Undertake special projects and ad‑hoc assignments as delegated by senior management
• Provide flexible support in response to evolving business and leadership needs

Requirements

• Minimum 5–8 years of experience in executive support, or management support roles
• Prior experience supporting C‑suite or senior leadership is strongly preferred
• Strong organisational, communication, and stakeholder management skills
• High level of discretion, integrity, and professionalism
• Ability to work independently in a fast‑paced,confidential environment
• Proficient in Microsoft Office and common business productivity tools

The Investment Manager is responsible for identifying, evaluating, and managing investment opportunities in line with the company’s strategic objectives. The role involves financial analysis, due diligence, execution support, and ongoing portfolio management.

Key Responsibilities

• Source, evaluate, and execute investment opportunities
• Conduct financial modelling, valuation, and investment analysis
• Perform due diligence, including commercial, financial, and risk assessments
• Prepare investment papers, presentations, and recommendations for senior management
• Monitor portfolio performance and support post-investment management
• Engage with external stakeholders such as advisors, partners, and co-investors
• Track market trends and provide strategic insights to support investment decisions

Requirements

• Bachelor’s degree in Finance, Economics, Business, or a related field
• Relevant experience in investment management, private equity, venture capital, corporate finance, or related areas
• Strong financial modelling and analytical skills
• Good understanding of capital markets and investment principles
• Excellent communication and stakeholder management skills

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 data analytics COE to fully incorporate Big data and Artificial Intelligence into strategic roadmap and enable digital transformation and smart manufacturing initiatives.

As the Data Scientist, she/he will apply advanced analytics techniques (e.g. machine learning and computer vision) into business context to transform data into meaningful and actionable insights that subsequently drive better and faster decision making. This role will build, validate and test prototype, get it to production ready phase and see through to the launch. This role will be working alongside bright minds across big data, software engineering and advanced analytics, and also be involved in research and development of cutting-edge data analytics techniques to support specific business requirements and products.

Main Responsibilities:

• Design and develop computer vision models for tasks such as detection, classification, segmentation, OCR, defect inspection, and visual tracking.
• Apply deep learning techniques (CNNs, Transformers, ViTs, multi-modal models) to real-world image and video data.
• Build end-to-end Vision AI pipelines from data collection, labeling, training, validation, to deployment.
• Work with project manager to translate requirements into Vision AI solutions.
• Optimize models for performance, accuracy, and inference speed in production environments (edge / cloud / hybrid).
• Integrate Vision AI with broader AI systems such as LLMs, RAG pipelines, or agentic workflows where relevant.
• Continuously evaluate and improve model robustness, bias, and generalization across scenarios.
• Document models, experiments, and best practices; contribute to internal AI standards and reuse libraries.

Job Requirements:

• At least Bachelor degree in Data Science, Applied Mathematics, Statistics, Computing Science, Electrical/Computer Engineering, Business Analytics.
• Minimum of 2 years of work experience in computer vision / Vision AI projects (industrial, medical, retail, manufacturing, etc.).
• Strong foundation in machine learning and deep learning, especially CV models (CNN, ResNet, YOLO, Faster R-CNN, UNet, ViT, etc.).
• Proficient in Python, PyTorch / TensorFlow, OpenCV.
• Experience with data annotation pipelines and tools (Label Studio, CVAT, etc.).
• Familiar with MLOps practices: experiment tracking, model versioning, CI/CD for ML.
• Experience deploying models with APIs, Docker, and cloud platforms (AWS / Azure / Alibaba Cloud).
• Strong problem-solving ability and ownership mindset.
• Ability to communicate clearly and effectively in both English and Mandarin.
• Willingness to travel up to 50%, depending on project needs, including site visits, customer workshops, and deployment support