- Leverage cutting-edge technologies: Utilize advanced technologies such as machine learning, deep learning, statistics, and operational research to innovate and optimize processes within the smart manufacturing domain. This includes tasks like data exploration, model development, and algorithmic decision-making.
- Application-driven analysis: Apply data analysis techniques to real-world applications including industrial inspection, defect classification, predictive maintenance, intelligent tuning, and parameter optimization, contributing directly to operational efficiency and product quality enhancement.
- Intellectual Property Creation: Contribute to the creation of Intellectual Property (IP) Rights in Singapore through innovative solutions and novel methodologies developed during research and development initiatives.
- Collaborative networking: Build and nurture relationships with local universities and research institutions to foster collaboration, resource integration, and the initiation of impactful projects that push the boundaries of smart manufacturing.
- Technical communication: Produce comprehensive technical reports and effectively collaborate with internal cross-functional teams to ensure alignment and dissemination of research findings and project outcomes.
- Integration with production needs: Understand and address the production requirements and challenges faced by business groups, integrating research and development insights seamlessly into the production line to drive tangible outcomes and business success.
- Research publication track record: Experience in publishing research papers within the domains of machine learning, deep learning, or data analysis, demonstrating a strong theoretical foundation and practical application expertise.
- Proficiency in tools and frameworks: Familiarity with a range of machine learning and data analysis tools and frameworks such as Scikit-learn, PyTorch, TensorFlow, Keras, OpenCV, among others, enabling efficient workflow execution and algorithm development.
- Understanding of distributed computing: Knowledge of distributed computing concepts and technologies such as Spark, Hadoop, Hive, etc., facilitating the processing and analysis of large-scale datasets and complex manufacturing data streams.
- Bonus experience: Additional experience in manufacturing practice, software development, digital twin simulation, and mechanism modeling is highly advantageous, contributing to a holistic skill set for tackling multifaceted challenges in smart manufacturing.
- Relevant experience: Minimum of 1 year of relevant experience in data science, machine learning, or related fields, showcasing practical application of skills and competencies in real-world settings.
- Language proficiency: Proficiency in both English and Mandarin, both spoken and written, to effectively communicate with diverse stakeholders and collaborate in a multicultural environment.
- Educational background: A minimum of a Master's degree in Computer Science Engineering or a related field, providing a solid foundation for advanced research and development activities within the smart manufacturing domain.
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Algorithm Design Engineer - Singapore - KERJA HOLDINGS PTE. LTD.
Description
Roles & ResponsibilitiesLocation: 3 Temasek Ave
Monday to Friday (8am to 530pm)
Job Description:
Preferred Qualifications:
EA License 22C1383
EA Personnel R
Tell employers what skills you haveTensorFlow
Machine Learning
Data Analysis
Modeling
OpenCV
Keras
Research and Development
PyTorch
Intellectual Property
Algorithm Development
Networking
Technical Communication
Statistics
Data Science
Manufacturing
Software Development
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