348 Natural Language jobs in Singapore

Overview
Global Talent Acquisition | HR Compliance & Payroll | Project Management
As a Research Scientist at MTRI, you will contribute to our mission of pushing AI forward in compliance-driven, high-stakes domains. You will be responsible for conducting original research, prototyping new systems, collaborating with other researchers, and bringing innovation from concept to impactful proof-of-concept.
Candidate Profile:
We welcome candidates who are in the final year of their Ph.D. program or recent Ph.D. graduates in Computer Science, Artificial Intelligence, Machine Learning, or related fields. Experienced researchers and industry professionals with strong publication records are also encouraged to apply.
Responsibilities
Conduct research in Natural Language Processing, Retrieval-Augmented Generation, Vision-Language Models, and other related fields;
Design, prototype, and evaluate novel algorithms and models;
Publish research findings in leading AI conferences and journals (e.g., NeurIPS, ICLR, CVPR, EMNLP, ACL, etc.);
Contribute to technology transfer by supporting proof-of-concept (POC) and pilot projects;
Represent the Company at international academic events;
Adhere to the highest standards of research ethics, data privacy, and compliance.
Qualifications
PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field
Hands-on experience in NLP methodologies (e.g., Text Classification, Supervised Fine-Tuning, Chain-of-Thought)
Seniority level
Internship
Employment type
Full-time
Industries
Research Services
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Our client is a fast-growing global software and AI company focused on building intelligent data platforms. Their technology helps organizations make smarter decisions through advanced analytics, automation, and machine learning. With teams across Asia and beyond, they combine strong engineering capabilities with a culture of curiosity, collaboration, and continuous learning to solve complex, real-world problems.
About the Role
My client is looking for a Senior Machine Learning Engineer to join their AI team and help build intelligent systems that power next-generation data and analytics platforms. You’ll develop machine learning and natural language models that enhance how our products understand, process, and generate insights from complex information.
Key Responsibilities
Design, develop, and optimize machine learning and NLP models for large-scale data analysis and language understanding.
Build and maintain training pipelines, covering data collection, cleaning, and validation.
Research and experiment with model optimization and fine-tuning techniques to improve performance.
Collaborate with product and engineering teams to deploy AI capabilities into real-world applications.
Stay up to date with AI trends and best practices, contributing to continuous improvement and innovation.
Requirements
Master’s or Bachelor’s degree in Computer Science, AI, Data Science, or related field.
5+ years of experience in machine learning, with exposure to NLP or LLM-based models.
Strong programming skills in Python and proficiency with frameworks such as PyTorch, TensorFlow, or JAX.
Solid understanding of transformer architectures (BERT, GPT, T5, etc.).
Familiarity with tools such as Hugging Face, LangChain, or similar ML libraries.
Experience with model deployment, optimization, and scalability is an advantage.
Why Join
You will be part of an ambitious AI team applying machine learning and NLP to solve real-world problems. This role offers the chance to work with cutting-edge technologies, collaborate with top engineers, and shape next-generation AI products in a dynamic, global environment.
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At Atomionics, we build quantum gravimeters that are set to revolutionize the resource exploration industry. We are looking for a motivated intern with experience in time-series machine learning to contribute to the development of our high-performance sensors.

Responsibilities

• Design and implement a machine learning model to map time-series data from support sensors to our quantum gravimeter data.

• Evaluate model performance on both synthetic and experimental datasets.

• Work closely with our multidisciplinary team to validate results and address challenges such as limited data coverage or overfitting.

• Visualise the performance of the model as well as intermediate outputs.

Qualifications

• Education background physics, engineering, or data science is highly desirable.

• Hands on experience with neural networks applicable to time-series data

• Strong Python programming skills: NumPy, SciPy, pandas, visualization packages

• Proficient with ML libraries such as PyTorch/TensorFlow/Keras, etc.

• Familiar with signal processing basics: Fourier transform, windowing, filtering

• Analytical mindset

What can we offer you

• A chance to learn about the intricacies of deep tech research, product development, and strategy in a high-growth startup
• Work on the cutting edge of quantum technology
• A book allowance to help you grow and collectively build the Atomionics library
• Board games and curry night

We're looking for an experienced Machine Learning Engineer to design, build, and deploy scalable ML solutions while ensuring compliance with AI governance and responsible AI practices. It covers the full ML lifecycle from data pipelines and ML Operations deployment to model monitoring and stakeholder collaboration in a global banking environment.

Client Details

Our client is a globally established financial institution with a major technology hub in Asia. They play a critical role in supporting international banking operations through the development of in-house applications and enterprise-level digital initiatives. With strong regional integration and a forward-looking tech strategy, they continue to enhance operational efficiency and drive innovation across global markets.

Description

Key Responsibilities:

• Partner with data scientists and business teams to define ML solutions and develop Proof of Concepts.
• Deploy and manage ML models in production using ML Operations best practices (CI/CD, monitoring, versioning).
• Build and maintain scalable data pipelines while ensuring model performance and reliability.
• Ensure compliance with AI governance, responsible AI practices, and audit requirements.
• Support data exploration, feature engineering, and model development when required.
• Automate retraining, testing, and monitoring to sustain long-term model accuracy.
• Document ML workflows and collaborate with DevOps, IT, and security teams for enterprise integration.

Profile

A successful candidate should have:

• Have Master's degree in AI/ML or data science with proven model design and development expertise.
• At least 6 years' experience in data science and ML, including at least 3 years in ML engineering roles.
• Hands-on experience across the full ML lifecycle: data preparation, model development, deployment, and monitoring.
• Strong Python programming skills and familiarity with ML frameworks (scikit-learn, TensorFlow, PyTorch).
• Proficiency in NoSQL databases (Graph DB experience a plus) and use of ML Operations tools (MLflow, Airflow, Kubeflow, etc.).
• Experience with cloud platforms (AWS, GCP, Azure), CI/CD pipelines, and containerization (Docker, Kubernetes).
• Knowledge of responsible AI practices, governance, compliance, and techniques like NLP, time series, and supervised/unsupervised learning.
• Strong problem-solving, communication, and collaboration skills, with the ability to explain technical concepts to non-technical stakeholders in diverse environments.

Job Offer

Why this role?

• Opportunity to work on cutting-edge AI/ML projects within a global banking environment
• Exposure to enterprise-scale ML Operations practices and full ML lifecycle implementation
• Career growth through continuous learning and professional development
• Competitive compensation and attractive benefits package
• Collaborative and multicultural workplace culture

To apply online please click the 'Apply' button. For a confidential discussion about this role please contact Cheryl Sim (Lic No: R / EA No.: 18C9065) on Michael Page International Pte Limited, company number N (including Page Executive A) and Page Personnel Recruitment Pte Ltd (Registration Number: C)) operates under the EA Licence Numbers of 18S9099 and 18C9065.

Responsibilities:

• Collaborate with data scientists and business stakeholders to define ML solutions and develop Proof of Concepts (PoCs).
• Engineer and deploy ML models into production using MLOps best practices (model versioning, monitoring, CI/CD).
• Build and maintain scalable data pipelines and monitor model performance.
• Ensure models comply with organizational AI policies, responsible AI practices, and audit requirements.
• Support data exploration, feature engineering, and occasional model building.
• Automate model retraining, testing, and monitoring to maintain long-term performance.
• Document ML workflows, governance checkpoints, and risk assessments.
• Partner with DevOps, IT, and security teams to integrate solutions into enterprise platforms.

Requirements:

• Masters degree in AI, ML, or Data Science.
• 6+ years in data science/ML, with 3+ years in ML engineering.
• Experience across the end-to-end ML lifecycle: data wrangling, model development, deployment, and monitoring.
• Strong Python programming skills (pandas, scikit-learn, TensorFlow/PyTorch).
• Experience with NoSQL databases; Graph database experience desirable.
• Hands-on with MLOps tools (MLflow, TFX, Airflow, Kubeflow, etc.).
• Familiarity with cloud platforms (GCP, AWS, Azure) for ML deployment.
• Solid knowledge of data science techniques (supervised/unsupervised learning, NLP, time series).
• Experience with CI/CD pipelines and containerization (Docker, Kubernetes).
• Understanding of AI governance, model risk management, and regulatory requirements.
• Ability to communicate technical concepts to non-technical stakeholders.

Preferred:

• Experience with Responsible AI frameworks and bias/fairness testing.
• Exposure to feature stores, model registries, and data versioning.
• Knowledge of data privacy, anonymization, and compliance in regulated industries (e.g., banking, healthcare).

To apply, please visit and search for Job Reference: 9396Y33Y

To learn more about this opportunity, please contact Yingying at

We regret that only shortlisted candidates will be notified.

GMP Technologies (S) Pte Ltd | EA Licence: 11C3793 | EA Personnel: Lai Yingying | Registration No: R

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By applying for this role, you consent to GMP Recruitment Services (S) Pte Ltds PDPA and e2is PDPA .

About Us

iCOMPASS Pte. Ltd. is a Singapore-headquartered RegTech company and spin-off from a leading advisory firm. iCOMPASS develops the world's first AI-powered compliance operating system designed for financial institutions. Designed in Singapore and built for global scalability, iCOMPASS is redefining how the financial industry approaches compliance in the age of AI.

Built at the intersection of regulatory expertise and cutting-edge technology, iCOMPASS transforms compliance from a reactive obligation into a proactive governance framework. With a vision to make regulatory compliance accessible, seamless, and adaptive, iCOMPASS empowers financial institutions of all sizes to reduce cost, mitigate risk, and enhance productivity.

Roles & Responsibilities

The successful candidate will design, build, and optimize LLM-driven solutions that support regulatory compliance, risk management. This role requires a deep understanding of both machine learning/NLP systems and compliance frameworks. The following summarises the scope of work:

• Model Development & Deployment

• Develop custom pipelines integrating structured (databases, transactions) and unstructured (news, documents, chat logs) data for compliance workflows.

• Implement explainability and interpretability layers to meet regulatory expectations.

• Compliance & Risk Applications

• Build systems that detect and classify financial crime risks (PEPs, RCAs, UBOs, sanctions exposure).

• Automate compliance document processing, regulatory reporting, and policy interpretation.

• Work closely with compliance officers to translate regulatory obligations into machine-executable rules.

• Systems Integration

• Deploy LLM-powered applications into enterprise-grade financial compliance platforms.

• Ensure robustness, scalability, and security of deployed models in production environments.

• Collaborate with engineering teams to integrate APIs, knowledge graphs, and third-party datasets.

• Research & Innovation

• Stay current with LLM advancements (RAG, fine-tuning, agents) and evaluate their applicability to compliance.

• Prototype tools for proactive risk detection and regulatory change monitoring.

• Others: Assist in ad-hoc projects or initiatives as assigned by management.

Requirements:

• Bachelor's Degree in Computer Science and any other relevant disciplines
• Strong analytical skills with the ability to assess risk and regulatory impact
• Ability to work independently and as part of a team in a fast-paced environment
• Excellent communication and presentation skills

Why Join Us?

• Engage in exciting projects to enhance compliance processes through innovation.
• Collaborative and dynamic work environment with opportunities for growth.
• We believe in rewarding impact and exceptional performance may be recognized with equity participation opportunities
• If you are looking to create impact in the regulated industry through technology transformation, this job is for you

If you are passionate about cross-pollinating regulatory compliance and technology, and enjoy problem-solving in a fast-paced environment, we invite you to apply for this role

Key Responsibilities

• Model Selection & Optimization: Identify, experiment with, and fine-tune state-of-the-art machine learning models for tasks such as video analytics, object recognition/detection, fraud detection, and multimodal generative AI.
• Deep Learning & LLMs: Work with transformer architectures, foundation models, and generative AI to develop and enhance multimodal AI solutions.
• Computer Vision: Develop and optimize models for real-time object detection, tracking, and recognition in video streams, ensuring performance in diverse conditions.
• Fraud Detection and other anomaly detection: Design and implement machine learning models for anomaly detection and fraud prevention using advanced statistical and AI techniques.
• Data Engineering & Processing: Preprocess large datasets, design efficient pipelines for real-time and batch processing, and integrate multimodal data sources (images, text, audio, video).
• Deployment & Scalability: Deploy models in production using cloud-based or edge computing solutions, ensuring performance, scalability, and cost-efficiency.
• Research & Innovation: Stay updated on the latest AI research, evaluate emerging models, and propose enhancements to improve performance and robustness.
• Collaboration & Integration: Work closely with software engineers, data scientists, and domain experts to integrate AI models into end-user applications.

Requirements

• Degree in Computer Science, AI, Machine Learning, or a related field.
• 4 to 5 years of relevant experience
• Strong experience in deep learning frameworks such as TensorFlow, PyTorch, or JAX.
• Proficiency in computer vision techniques, including object detection (YOLO, Faster R-CNN), video analytics, and multimodal learning.
• Hands-on experience with LLMs, transformers (GPT, BERT, T5, CLIP, etc.), and multimodal AI for text, image, and video synthesis.
• Experience in fraud detection and/or anomaly detection using machine learning, pattern recognition, and risk modeling.
• Experience in AWS SageMaker for model training and deployment preferred.
• Familiarity with MLOps and deployment on cloud platforms (AWS and/or GCP preferred) or edge devices.
• Strong problem-solving and analytical thinking abilities.
• Ability to work in a fast-paced, research-driven environment and adapt to evolving challenges.
• Excellent communication skills for presenting findings and collaborating across teams.
• Experience working with autonomous systems, robotics, or edge AI is a plus.

Interested parties, please click the "Apply Now" below AND apply via the GO portal.

We regret that only shortlisted applicants would be notified.

Toh Wen Qi, Celeste | REG No : R

PERSOLKELLY SINGAPORE PTE LTD | EA License No : 01C4394

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• Opportunity to work in a Global Financial Institution
• Deliver transformative IT solutions that enhance operational efficiency.

Our client is a globally established financial institution with a major technology hub in Asia. They play a critical role in supporting international banking operations through the development of in-house applications and enterprise-level digital initiatives. With strong regional integration and a forward-looking tech strategy, they continue to enhance operational efficiency and drive innovation across global markets.

Key Responsibilities:

• Partner with data scientists and business teams to define ML solutions and develop Proof of Concepts.
• Deploy and manage ML models in production using ML Operations best practices (CI/CD, monitoring, versioning).
• Build and maintain scalable data pipelines while ensuring model performance and reliability.
• Ensure compliance with AI governance, responsible AI practices, and audit requirements.
• Support data exploration, feature engineering, and model development when required.
• Automate retraining, testing, and monitoring to sustain long-term model accuracy.
• Document ML workflows and collaborate with DevOps, IT, and security teams for enterprise integration.

A successful candidate should have:

• Have Master's degree in AI/ML or data science with proven model design and development expertise.
• At least 6 years' experience in data science and ML, including at least 3 years in ML engineering roles.
• Hands-on experience across the full ML lifecycle: data preparation, model development, deployment, and monitoring.
• Strong Python programming skills and familiarity with ML frameworks (scikit-learn, TensorFlow, PyTorch).
• Proficiency in NoSQL databases (Graph DB experience a plus) and use of ML Operations tools (MLflow, Airflow, Kubeflow, etc.).
• Experience with cloud platforms (AWS, GCP, Azure), CI/CD pipelines, and containerization (Docker, Kubernetes).
• Knowledge of responsible AI practices, governance, compliance, and techniques like NLP, time series, and supervised/unsupervised learning.
• Strong problem-solving, communication, and collaboration skills, with the ability to explain technical concepts to non-technical stakeholders in diverse environments.

Why this role?

• Opportunity to work on cutting-edge AI/ML projects within a global banking environment
• Exposure to enterprise-scale ML Operations practices and full ML lifecycle implementation
• Career growth through continuous learning and professional development
• Competitive compensation and attractive benefits package
• Collaborative and multicultural workplace culture

Michael Page International Pte Ltd | Registration No. N