Machine Learning Engineer

PLUANG TECHNOLOGIES PTE. LTD.; Singapore; On-site; SGD 50,000 - 70,000; Full time

Job summary

A financial technology company in Singapore is seeking a Machine Learning Engineer to develop AI-powered systems for financial analysis and decision-making. You will collaborate with experienced teams to build solutions, leveraging machine learning techniques to address complex financial challenges. Ideal candidates will have a degree in a quantitative field, some programming experience, and a keen interest in financial markets.

Qualifications

• 0-2 years of experience in machine learning, data science, or software engineering (internships count).
• Interest in Large Language Models and AI techniques.
• Experience with data manipulation and basic feature engineering.

Responsibilities

• Assist in designing and implementing machine learning solutions for financial markets.
• Support the development of intelligent systems using machine learning approaches.
• Contribute to building ML pipelines for model development and deployment.

Skills

Programming skills in Python

Foundational knowledge of machine learning

Strong mathematical and analytical foundation

Good communication skills

Curiosity about financial markets

Education

Bachelor's or Master's degree in Computer Science, Machine Learning, or related field

Tools

pandas

numpy

scikit-learn

Git

Job description

As a Machine Learning Engineer (Trading & Financial Intelligence), you will contribute to the development of AI‑powered systems and autonomous agents that transform how financial analysis and decision‑making are conducted. Working under the guidance of senior team members, you will help build intelligent solutions that analyze markets, extract insights from financial data, and support risk management using machine learning and quantitative techniques. This role offers an excellent opportunity to learn and apply both traditional ML and modern LLM‑based approaches to solve real financial problems while collaborating with experienced trading, research, and product teams.

What You Will Be Doing:

• Assist in designing and implementing machine learning solutions for financial markets, from predictive models to AI agents powered by LLMs
• Support the development of intelligent systems using traditional ML approaches (time series analysis, anomaly detection, pattern recognition) and modern agentic frameworks
• Help apply quantitative methods and data mining techniques to extract insights from financial datasets under senior guidance
• Contribute to building ML pipelines for model development, backtesting, and production deployment with monitoring frameworks
• Support research platforms that enable experimentation with both classical statistical models and LLM‑based approaches for financial analysis
• Work closely with traders, quants, researchers, and senior engineers to understand and help solve complex financial problems
• Assist in developing risk assessment and portfolio optimization systems using quantitative methods and AI‑driven approaches
• Participate in code reviews, documentation, and knowledge sharing to continuously improve technical skills

What You Need to Be Successful in This Role:

• We welcome all applicants who are eligible to work in Singapore
• Bachelor's or Master's degree in Computer Science, Machine Learning, Statistics, Mathematics, Physics, Financial Engineering, or related quantitative field
• 0-2 years of professional experience in machine learning, data science, or software engineering (internships, projects, and academic experience count)
• Solid programming skills in Python with familiarity with scientific computing libraries (pandas, numpy, scikit-learn)
• Foundational knowledge of machine learning including supervised/unsupervised learning, basic deep learning concepts, and statistical modeling
• Interest in Large Language Models and modern AI techniques - experience with prompt engineering, fine‑tuning, or agentic systems is a plus but not required
• Strong mathematical and analytical foundation with ability to learn and apply quantitative concepts to practical problems
• Experience with data manipulation and basic feature engineering from structured datasets
• Eagerness to learn with ability to work collaboratively in a mentorship‑oriented environment
• Good communication skills to discuss technical concepts and ask questions effectively
• Basic understanding of software engineering practices including version control (Git) and testing
• Curiosity about financial markets - prior knowledge of trading systems or quantitative finance is beneficial but not required
• Academic or personal projects demonstrating ML skills through coursework, competitions, or self‑directed learning

If you have recently applied for this position, we have your application on file and will contact you if there is a suitable match.