Total 137 software test engineer job vacancies in Education / Training category

Candidate shall lead and conduct research in development of AI-based robotic solutions particularly for manufacturing processes that deliver impactful research and industry deployment outcomes.

Key Role & Responsibilities:

• Lead stakeholder discussions to grasp problem statements, requirements, and expectations.
• Develop project proposals and scoping.
• Collaborate with multidisciplinary technology groups in development of robotic solution from design conceptualization to prototyping and factory deployment.
• Explore, evaluate and propose research based topics in alignment with RIE2030.

Requirements:

• Relevant Engineering degree with focus on robotics or mechatronics.
• Minimal 10 years of industry experience in manufacturing process automation. Preferably in automotive production, aerospace MRO, biomedical production/laboratory.
• Proficient in 3D modeling CAD software.
• Essential IT/OT integration know-how towards digital transformation.
• Basic knowledge in machine learning frameworks and modelling.
• Effective communication and stakeholder interaction abilities.
• Adaptable, hands-on, and self-motivated approach to work.

The above eligibility criteria are not exhaustive. A*STAR may include additional selection criteria based on its prevailing recruitment policies. These policies may be amended from time to time without notice. We regret that only shortlisted candidates will be notified.

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 inconsistency scores. 

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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.

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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.