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- Build and improve machine learning and analytics platform.
- Apply cutting edge technologies and tool chain in big data and machine learning to build machine learning and analytics platform.
- Keep innovating and optimizing the machine learning workflow, from data exploration, model experimentation/prototyping to production.
- Provide engineering solution and framework to support machine learning and data-driven business activities at large scale.
- Perform R&D on new technologies and solutions to improve accessibility, scalability, efficiency and abilities of machine learning and analytics platform.
- Work with data scientists to build end-to-end machine learning and analytics solution to solve business challenges.
- Turn advanced machine learning models created by data scientists into end-to-end production grade system.
- Build analytics platform components to support data collection, exploratory, and integration from various sources being data API, RDBMS, or big data platform.
- Optimize efficiency of machine learning algorithm by applying state-of-the-art technologies, , concurrent programming, or GPU parallel computing.
- Establish, apply and maintain best practices and principles of machine learning engineering.
- Study and evaluate the state of the art technologies, tools, and frameworks of machine learning engineering.
- Contribute in creation of blueprint and reference architecture for various machine learning use cases.
- Support the organization in transformation towards a data driven business culture.
- Internal - Work closely with data scientists, business team, and project managers to provide machine learning and data-driven business solution.
- Collaborate with other technology teams to build platform and framework to enable machine learning and data analytics activities at large scale
- External - Maintain engineering principles and best practices of machine learning framework and technologies.
- PhD/Masters/Bachelors in Computer Science, Computer Engineering, Statistics, Applied Mathematics, or related disciplines.
- 10+ years of experience in software engineering or DevOps automation or data engineering
- Excellent understanding of software engineering principles and design patterns.
- Excellent programming skills in either Python or Java.
- Hands-on experience in containerization/ virtualization platforms,
- Exposure to data science and machine learning technologies and methodologies.
- Good working knowledge of high performance computing, parallel data processing, and big data stack,
- Experience to one or more commercial / open source data warehouses or data analytics systems, , is a big plus.
- Experience to one or more NoSQL databases is a big plus.
- Experience or Cloudera Data Science Workbench, is a big plus.
- Passion about machine learning and data-driven intelligence system.
- Excellent communication and presentation skills.
- Team player, self-starter, ability to work on multiple projects in parallel is necessary.
- Experience working in multi-cultural environments
Machine Learning Engineer - Singapur, Singapore - DBS Bank
Description
Business Function
Group Technology and Operations (T&O) enables and empowers the bank with an efficient, nimble and resilient infrastructure through a strategic focus on productivity, quality & control, technology, people capability and innovation. In Group T&O, we manage the majority of the Bank's operational processes and inspire to delight our business partners through our multiple banking delivery channels.
Responsibilities
Work Relationships
Requirements