AI Researcher: LLM-Driven Analytics & Agents

KLASS ENGINEERING & SOLUTIONS PTE. LTD.; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

KLASS ENGINEERING & SOLUTIONS PTE. LTD. is seeking an AI researcher to design and build non-deterministic analytical tools based on statistical modelling, predictive models, and machine learning across structured and unstructured data.

The role includes developing AI agents powered by large language models that can reason over and orchestrate these tools to solve analytical problems end-to-end. The researcher will apply rigorous data practices, explore intelligent systems, and pursue solutions

Qualifications

• Master’s or PhD in Computer Science, Mathematics, Statistics, Physics, Engineering, Data Science, or closely related field.
• Strong Python programming with data science libraries (Pandas, NumPy, Scikit-learn, Matplotlib/Seaborn).
• Experience with data wrangling, missing data handling, feature engineering, and normalization on structured datasets.
• Foundations in linear algebra, calculus, and optimization applied to ML and statistics.

Responsibilities

• Conduct research to identify patterns, trends, and statistically significant findings to inform decisions.
• Develop predictive models and mathematical approaches for defined problems.
• Design and run experiments, validate model performance, and report limitations.
• Collaborate to study LLM-based agents, automate research workflows, and present findings.

Skills

Python

Data Wrangling

ML & Modelling

Statistical Methods

Education

Master’s or PhD in a quantitative field

Job description

KLASS ENGINEERING & SOLUTIONS PTE. LTD. is seeking an AI researcher to design and build non-deterministic analytical tools based on statistical modelling, predictive models, and machine learning across structured and unstructured data.

The role includes developing AI agents powered by large language models that can reason over and orchestrate these tools to solve analytical problems end-to-end. The researcher will apply rigorous data practices, explore intelligent systems, and pursue solutions