Senior Machine Learning Engineer II

PLUANG TECHNOLOGIES PTE. LTD.; Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

A technology financial firm in Singapore is seeking a Senior Machine Learning Engineer to develop AI-powered systems for transforming financial analysis and decision-making. The role involves building intelligent solutions, collaborating with various teams, and utilizing advanced machine learning techniques. Candidates should have a solid background in machine learning, strong programming skills in Python, and a Bachelor's or Master's degree in a related field.

Qualifications

• 3+ years of experience in machine learning engineering or data science.
• Strong programming skills in Python with relevant libraries.
• Familiarity with Large Language Models and modern AI techniques.

Responsibilities

• Design and implement machine learning solutions for financial markets.
• Develop intelligent systems using traditional ML approaches.
• Collaborate with traders and researchers to create scalable ML solutions.

Skills

Python programming

Machine learning techniques

Quantitative analysis

Data mining

Statistical modeling

Communication skills

Education

Bachelor's or Master's degree in Computer Science or related field

Tools

pandas

numpy

scikit-learn

Job description

Overview

As a Senior Machine Learning Engineer (Trading & Financial Intelligence), you will develop AI-powered systems and autonomous agents that transform how financial analysis and decision-making are conducted. You will build intelligent solutions that analyze markets, extract insights from complex financial data, and assist with risk management using advanced ML and quantitative techniques. This role offers the opportunity to apply cutting-edge AI, from traditional machine learning to modern LLM-based agents, to solve complex financial problems while collaborating with trading, research, and product teams.

What You Will Be Doing

• Design and implement machine learning solutions for financial markets, ranging from predictive models to autonomous AI agents powered by LLMs
• Develop intelligent systems using both traditional ML approaches (time series analysis, anomaly detection, pattern recognition) and modern agentic frameworks (LangChain, reasoning loops, tool orchestration)
• Apply quantitative methods and data mining techniques to extract actionable insights from large-scale financial datasets
• Build end-to-end ML pipelines for model development, backtesting, and production deployment with robust monitoring and evaluation frameworks
• Create research platforms that enable rapid experimentation with both classical statistical models and LLM-based approaches for financial analysis
• Collaborate with traders, quants, and researchers to translate complex financial problems into scalable ML solutions
• Develop risk assessment and portfolio optimization systems using a combination of traditional quantitative methods and AI-driven approaches

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
• 3+ years of experience in machine learning engineering, quantitative research, or data science with production systems
• Strong programming skills in Python with expertise in scientific computing libraries (pandas, numpy, scikit-learn) and ML frameworks
• Experience with diverse ML techniques including supervised/unsupervised learning, deep learning, time series forecasting, and statistical modeling
• Familiarity with Large Language Models and modern AI techniques, including prompt engineering, fine-tuning, and agentic systems is highly valued
• Strong quantitative and analytical skills with ability to apply mathematical and statistical concepts to real-world problems
• Experience with data mining and feature engineering from large, complex datasets
• Problem-solving mindset with the ability to work independently and in fast-paced, results-oriented environments
• Good communication skills to present technical findings to both technical and non-technical stakeholders
• Knowledge of financial markets, trading systems, or quantitative finance is a plus but not required - we value strong technical skills and learning ability
• Experience with backtesting frameworks, risk modeling, or portfolio optimization is beneficial
• Interested candidates, please click the link to apply: https://pluanghrms.darwinbox.com/ms/candidate/careers/a68b0059d2bb11