155 AI Program Manager jobs in Singapore

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

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

(What the role is)

The Enterprise Knowledge Department (EKD) is seeking an innovative Generative AI Engineer to join our Data & Tech Solutions team. As part of the Economics & Knowledge Management Group, you'll work with a dynamic team passionate about revolutionising how we manage, discover, and generate data through cutting-edge AI solutions. You'll thrive in our fast-paced environment where adaptability and multi-tasking are essential.

(What you will be working on)

As a Generative AI Engineer, you will architect and deploy state-of-the-art generative AI models that transform how we create, process, and retrieve information. You will work at the intersection of large language models, content generation, and business automation, collaborating with cross-functional teams to deliver innovative solutions.

Key Responsibilities:

• Design and implement generative AI solutions that align with business requirements and use cases
• Develop and optimise large language models and generative AI architectures for text, code, and data generation
• Fine-tune and deploy foundation models while ensuring responsible AI practices and ethical considerations
• Create and maintain prompt engineering frameworks and evaluation metrics
• Build robust AI pipelines that integrate with existing systems and workflows
• Conduct experiments to improve model performance, efficiency, and output quality
• Implement safeguards and controls for AI-generated content
• Stay current with rapid developments in generative AI and implement emerging best practices
• Collaborate with stakeholders to identify opportunities for AI-driven process automation

(What we are looking for)

• Degree in Computer Science, AI/ML, or related field. Advanced degree is a plus
• Strong programming skills in Python, with experience in modern AI frameworks (PyTorch, TensorFlow, Hugging Face)
• Hands-on experience with large language models (e.g., GPT family, BERT, T5)
• Understanding of transformer architectures, attention mechanisms, and prompt engineering
• Experience with model fine-tuning, few-shot learning, and prompt optimization
• Familiarity with AI deployment platforms and MLOps practices
• Knowledge of responsible AI principles and ethical considerations
• Proficiency with version control and collaborative development workflows
• Experience with API development and integration
• Strong problem-solving abilities and analytical mindset
• Excellent communication skills for technical and non-technical audiences
• Self-motivated with the ability to work independently

As part of the shortlisting process for this role, you may be required to complete a medical declaration and/or undergo further assessment.

All applicants will be notified on whether they are shortlisted or not within 4 weeks of the closing date of this job posting.

We are seeking an experienced Machine Learning / AI Engineer to drive innovative digital initiatives across global projects. In this role, you will design, build, and deploy end-to-end machine learning solutions that are scalable, reliable, and compliant with AI governance and regulatory standards.

Key Responsibilities

• Collaborate with data scientists and business teams to define and implement ML solutions.
• Develop and deploy production-grade models using MLOps best practices (CI/CD, versioning, monitoring).
• Build and maintain data and model pipelines for scalability and performance.
• Ensure compliance with responsible AI, governance, and audit requirements.
• Automate retraining, testing, and monitoring of deployed models.
  Partner with DevOps, IT, and security teams for seamless integration.

Qualifications

• Master's degree in AI, ML, or Data Science.
• 6+ years in data science and ML, including 3+ in ML engineering.
• Proficiency in Python (pandas, scikit-learn, TensorFlow, PyTorch).
• Experience with MLOps tools (MLflow, Airflow, Kubeflow, etc.) and cloud platforms (AWS, Azure, GCP).
• Knowledge of CI/CD, Docker, Kubernetes, and NoSQL databases.
• Strong understanding of AI governance, model risk, and compliance.
  Excellent communication and problem-solving skills.

Preferred: Experience with Responsible AI, bias testing, feature stores, and data privacy in regulated sectors.

For a confidential discussion, please reach out to me at

Personal data collected will be used for recruitment purposes only.

Only shortlisted candidates will be notified / contacted.

EA Registration No: R

"Sanderson-iKas" is the brand name for iKas International (Asia) Pte Ltd, a company incorporated in Singapore under Company UEN No.: E with EA license number 16S8086.

Website:

• Have Master's degree in the field of AI / ML and data science with proven ability to design and develop models

• 6+ years of experience in data science and machine learning, with at least 3+ years in ML engineering roles.

• Proven experience in end-to-end ML lifecycle: data wrangling, model development, deployment, and monitoring.

• Strong programming skills in Python (pandas, scikit-learn, TensorFlow/PyTorch, etc.).

• Strong knowledge in NoSQL databases (any experience in Graph database is desirable)

• Experience with MLOps tools: MLflow, TFX, Airflow, Kubeflow, or similar.

• Familiarity with cloud platforms (GCP, AWS, or Azure) for ML deployment.

• Knowledge of data science techniques including supervised/unsupervised learning, NLP, time series, etc.

• Experience with CI/CD pipelines and containerization (Docker, Kubernetes).

• Strong understanding of AI governance, model risk management, and regulatory requirements in AI.

• Ability to communicate technical concepts to non-technical stakeholders.

Support Project/System implementation of Machine Learning Suite (MLS)

Ensure solution design complies with enterprise design principles, security and control standards

Convert business requirements to design document and other system documentation to capture key design decisions

Able to conduct data mapping and process mapping with interfacing applications

Create technical documents for the solutions

Conduct root cause analysis of issues, review new and existing code and/or perform unit testing

Work with Test Management teams to complete SIT/UAT as planned

Manage project change request approval windows and deployment schedule

Facilitate and provide technical and testing support before and after production deployment

Manage external vendors for project delivery within schedule

a, Experience end-to-end projects for system implementation of Machine Learning Suite (MLS)

b. Strong in driving project deliverables, actively tracking timelines, escalating issues when needed, and ensuring accountability across teams.

c. Strong in Project Management, Financial Management, Application Management, Risk and Issue Management, Change Management and Resource Management

d. experience in application architecture, development, system integration and software design

e.Experience in Production Support Management, Incident and Problem Management

f. Knowledge in networking, firewall, data migration, password encryption, SSO integration, and disaster recovery planning and testing

Job Type: Contract

Contract length: 12 months

Benefits:

• Health insurance

Work Location: In person

a, Experience end-to-end projects for system implementation of Machine Learning Suite (MLS)

b. Strong in driving project deliverables, actively tracking timelines, escalating issues when needed, and ensuring accountability across teams.

c. Strong in Project Management, Financial Management, Application Management, Risk and Issue Management, Change Management and Resource Management

d. experience in application architecture, development, system integration and software design

e.Experience in Production Support Management, Incident and Problem Management

f. Knowledge in networking, firewall, data migration, password encryption, SSO integration, and disaster recovery planning and testing

Support Project/System implementation of Machine Learning Suite (MLS)

Ensure solution design complies with enterprise design principles, security and control standards

Convert business requirements to design document and other system documentation to capture key design decisions

Able to conduct data mapping and process mapping with interfacing applications

Create technical documents for the solutions

Conduct root cause analysis of issues, review new and existing code and/or perform unit testing

Work with Test Management teams to complete SIT/UAT as planned

Manage project change request approval windows and deployment schedule

Facilitate and provide technical and testing support before and after production deployment

Manage external vendors for project delivery within schedule

Job Type: Contract

Contract length: 12 months

Benefits:

• Health insurance

Work Location: In person

Custom Field 1: Singapore Exchange

Location:
Singapore, SG

Facility: Operations & Technology

Job Type: Contract (Project IO)

Custom Field 2: 2927

SGX is looking for a Machine Learning Engineer who is passionate about building scalable data/machine learning platforms and pioneering solutions. As a Machine Learning Engineer, you will play a crucial role in transforming how we run and deploy AI/ML models. Your work will directly impact our ability to build and deliver AI/ML use cases that will augment our users in their work or enable business opportunities. By enhancing our machine learning platform, you will enable us to make data-driven decisions and drive innovation across the organization. This is a 2-year contract role with an option for extension.

• Design and build scalable data platforms (including machine learning platforms) to support AI/GenAI use cases, streamline data storage, democratization, model deployment, and support feature engineering, model training, deployment, model monitoring and inference.
• Develop and integrate data pipelines for continuous development, integration, testing, and scalable machine learning services.
• Migrate existing data science projects to the new cloud machine learning platform.
• Collaborate with data scientists and data engineers to design, implement, and integrate data pipelines.
• Improve/automate existing model training, feature engineering, and evaluation pipelines, enabling the feedback loop of taking in labelled data from users/source systems for model re-training/tuning.
• Design and develop CI/CD pipeline, consistent logging, tracking, and monitoring of pipelines and model performance to ensure consistent model performance and alert mechanisms for model drift.
• Support data extraction and transformation for projects and users' needs.
• Review, support, improve, and run the platform, including the existing data platform/machine learning server, and environment management.
• Provide support for data-related queries, extraction, and discrepancies.
• Stay abreast of and analyze industry developments to identify areas of continuous improvement.

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• 2-4 years of experience in setting up a machine learning platform, developing and deploying machine learning models and AI solutions.
• Familiarity with machine learning platforms, LLM, Lang Chain.
• Proficiency in Python, SQL, and modern AI/ML algorithms, with experience in deploying solutions into production. Experience with GCP/Vertex AI is a plus.
• Highly driven, proactive, and a strong team player. Excellent interpersonal, written, and verbal communication skills in English. Ability to multitask effectively and handle large amounts of data.

Job Segment: Computer Science, Database, SQL, Learning, Technology, Human Resources

Pluang Technologies Pte. Ltd., Singapore, Singapore, Singapore

Department

Machine Learning

Job posted on

Aug 28, 2025

Employment type

Full Time

As a Machine Learning Engineer (Trading & Financial Intelligence), you will contribute to the development of AI-powered systems and autonomous agents that transform how financial analysis and decision-making are conducted. Working under the guidance of senior team members, you will help build intelligent solutions that analyze markets, extract insights from financial data, and support risk management using machine learning and quantitative techniques. This role offers an excellent opportunity to learn and apply both traditional ML and modern LLM-based approaches to solve real financial problems while collaborating with experienced trading, research, and product teams.

What You Will Be Doing:

• Assist in designing and implementing machine learning solutions for financial markets, from predictive models to AI agents powered by LLMs
• Support the development of intelligent systems using traditional ML approaches (time series analysis, anomaly detection, pattern recognition) and modern agentic frameworks
• Help apply quantitative methods and data mining techniques to extract insights from financial datasets under senior guidance
• Contribute to building ML pipelines for model development, backtesting, and production deployment with monitoring frameworks
• Support research platforms that enable experimentation with both classical statistical models and LLM-based approaches for financial analysis
• Work closely with traders, quants, researchers, and senior engineers to understand and help solve complex financial problems
• Assist in developing risk assessment and portfolio optimization systems using quantitative methods and AI-driven approaches
• Participate in code reviews, documentation, and knowledge sharing to continuously improve technical skills

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
• 0-2 years of professional experience in machine learning, data science, or software engineering (internships, projects, and academic experience count)
• Solid programming skills in Python with familiarity with scientific computing libraries (pandas, numpy, scikit-learn)
• Foundational knowledge of machine learning including supervised/unsupervised learning, basic deep learning concepts, and statistical modeling
• Interest in Large Language Models and modern AI techniques - experience with prompt engineering, fine-tuning, or agentic systems is a plus but not required
• Strong mathematical and analytical foundation with ability to learn and apply quantitative concepts to practical problems
• Experience with data manipulation and basic feature engineering from structured datasets
• Eagerness to learn with ability to work collaboratively in a mentorship-oriented environment
• Good communication skills to discuss technical concepts and ask questions effectively
• Basic understanding of software engineering practices including version control (Git) and testing
• Curiosity about financial markets - prior knowledge of trading systems or quantitative finance is beneficial but not required
• Academic or personal projects demonstrating ML skills through coursework, competitions, or self-directed learning

Senior Machine Learning Engineer II

Pluang Technologies Pte. Ltd., Singapore, Singapore, Singapore