Machine Learning Engineer
Location:
Singapore
Employment Type:
Full-Time
Experience Level:
Mid to Senior Level
Job Description
We are seeking a dedicated and experienced Machine Learning Engineer to join our growing team. The ideal candidate will be responsible for the end-to-end lifecycle of Machine Learning (ML) systems—from requirement gathering and design to development, testing, deployment, and maintenance.
This role involves close collaboration with both internal and external stakeholders, and offers the opportunity to contribute to innovative projects that integrate cutting-edge ML and AI technologies across various domains.
Key Responsibilities
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Collaborate with internal teams, external partners, and clients to gather requirements and design ML system architectures.
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Develop, test, deploy, and maintain Machine Learning models and systems aligned with project objectives and business needs.
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Document system specifications, processes, and technical decisions to ensure knowledge retention and transferability.
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Explore, evaluate, and integrate emerging ML tools, libraries, platforms, and frameworks.
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Support the creation and maintenance of an ML/AI knowledge base to enhance team capabilities and innovation.
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Contribute to pre-sales activities, including proposal development and technical demonstrations.
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Provide post-sales technical support and assist in system integration and deployment.
Job Requirements
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Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
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Recognized certifications in Machine Learning technologies or relevant technical competencies are highly desirable.
- 3–5 years of hands-on experience in the design and development of Machine Learning systems in a professional setting.
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Strong expertise in at least two of the following areas:
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Data Modelling
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Data Mining
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Statistical Analysis
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Simulation
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Operations Research
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Data Visualization
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Predictive Analytics
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Proficiency in programming languages such as Python, R, SQL, Java, C/C++, MATLAB, or Scala .
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Familiarity with big data technologies including Hadoop, Spark, Hive, HBase is an added advantage.
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Knowledge of cloud platforms such as AWS, Google Cloud Platform, or Microsoft Azure is a plus.
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Practical experience with Agile methodologies and working within an iterative development environment.
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Understanding of MLOps best practices , including CI/CD pipelines, model deployment, version control, and lifecycle management.
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Excellent written and verbal communication skills, with the ability to convey complex technical concepts clearly and effectively.
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Strong analytical thinking, interpersonal skills, and a proactive problem-solving approach.
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Self-motivated, organized, and able to work independently or as part of a collaborative, fast-paced team.
Join Us
If you are passionate about Machine Learning and thrive in a challenging and forward-thinking environment, we invite you to apply and contribute to impactful projects at the forefront of data and AI innovation.
