Research Engineer (in accounting and NLP/AI) - BRC

Singapore Institute of Technology; Singapore; On-site; SGD 56,000 - 89,000; Full time

Job summary

Singapore Institute of Technology invites a Research Engineer to join a MOE AcRF Tier 1 funded project spanning accounting and NLP/AI. You will design, build, and validate pipelines that detect inconsistencies between financial filings and earnings call transcripts, using retrieval-augmented NLI models and LLMs on large-scale financial text data.

The role involves implementing retrieval systems, processing data, and supporting empirical analysis of contradiction scores, with emphasis on

Qualifications

• Bachelor’s or Master’s in CS/IS/AI or related field.
• Strong Python programming and NLP foundations.
• Familiarity with ML/NLP libraries and model deployment concepts.
• Experience with version control (Git) and collaborative projects.

Responsibilities

• Drive the technical execution of the research project under PI/Co-PI guidance.
• Design and implement retrieval-augmented NLI pipeline for detecting inconsistencies across disclosures and transcripts.
• Preprocess large-scale financial text data and index corpora.
• Implement and evaluate claims extraction using LLM-based approaches.
• Develop semantic retrieval for claim-context matching across channels.
• Build and assess contradiction detection models using NLI/LiM prompting.
• Assemble firm-quarter level scores and datasets for analysis.
• Coordinate with student annotators and prepare annotation guidelines.
• Maintain reproducible workflows with version control and documentation.

Skills

Python programming

NLP

Machine learning

Information retrieval

Git

Team collaboration

Education

Bachelor’s or Master’s in Computer Science or related field

Tools

HuggingFace Transformers

PyTorch

TensorFlow

scikit-learn

Job description

Job Description

Research Engineer (in accounting and NLP/AI) - BRC

Posting Start Date: 07/04/2026

Schemes of Service: Research

Division: Business, Communication and Design

Employment Type: Fixed Term

We are looking for a Research Engineer to join our MOE AcRF Tier 1 funded research project at the Singapore Institute of Technology. You will be part of an interdisciplinary team spanning accounting and NLP/AI, working to design, build, and validate a pipeline that detects inconsistencies and contradictions between firms' written financial filings (10-K/10-Q) and spoken earnings call transcripts. The role involves implementing retrieval-augmented natural language inference models and LLMs, processing large-scale financial text data, and supporting empirical analysis of contradiction scores.

Job Responsibilities

• Drive the technical execution of the research project under the guidance of the PI and Co-PI, ensuring project deliverables and timelines are met.
• Design and implement the retrieval-augmented NLI pipeline for inconsistency and contradiction detection across corporate disclosures (earnings call transcripts and SEC filings).
• Perform large-scale text preprocessing, cleaning, segmentation, and indexing of earnings call transcripts and financial filing corpora.
• Implement claims extraction modules using LLM-based approaches to identify key assertions from corporate disclosures.
• Build semantic retrieval mechanisms (e.g., Sentence-BERT embedding similarity search) for matching claim-context pairs across disclosure channels.
• Implement and evaluate contradiction detection models using NLI frameworks and LLM prompting techniques.
• Aggregate model outputs into firm-quarter level scores and prepare structured datasets for empirical analysis.
• Support human-in-the-loop validation by coordinating with student annotators and preparing annotation guidelines.
• Maintain reproducible research workflows using version control (Git) and systematic documentation of processes, code, and findings.

Job Requirements

• Bachelor’s degree or Master’s degree in Computer Science, Information Systems, Data Science, Artificial Intelligence, or a closely related field.
• Strong programming skills in Python, with experience in relevant libraries such as HuggingFace Transformers, PyTorch/TensorFlow, and scikit-learn.
• Prior experience or coursework in natural language processing, machine learning, or information retrieval.
• Familiarity with version control tools (e.g., Git/GitHub) and collaborative development practices.
• Experience with financial data or financial text analysis will be advantageous.
• Familiarity with LLM APIs, prompt engineering, and retrieval-augmented generation (RAG) workflows will be advantageous.
• Good communication skills and ability to work both independently and collaboratively.