231 Machine Learning Algorithms jobs in Singapore

• 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

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

Responsibilities

Our team is responsible for providing TikTok search users with first-class search experience by building a strong and robust infrastructure and platform to support product fast iteration and key feature development. In our team, you'll have the opportunity to take part in developing the key features on TikTok Search, understand how TikTok Search could be evolved to be a multi-billion-user product and first-handed experience how user request varies on this giant from time to time. We encourage a culture of self-driven, intellectual curiosity, openness and problem-solving.
Responsibilities
- Optimize the search quality in poi and local service, provide TikTok's users the best search experience
- Combine your understanding of product objectives and take full advantage of modern machine learning, NLP and Multimodal techniques to improve the search result metrics
- Work with products and DAs, and other engineers to deliver features to drive the experience optimization of products.
Qualifications

Minimum Qualifications:
-Bachelor degree or above in the field of computer science or a related technical discipline
-Proficient coding skills and strong algorithm & data structure basis in C++/Python/Java
-Experience in one or more of the following areas: NLP, Ranking, Ads, Search engine, Recommender System, and Machine Learning
-Effective communication and teamwork skills.
Preferred Qualifications
- Passion for technology, good communication skills and team spirit

About Us

Location: Shanghai

At Qubot, we are committed to build advanced technologies to save lives. We build neuro-interventional robot to automate mechanical thrombectomy. We have a strong team of deep learning scientists, software engineers, hardware engineers and material engineers, and are currently inviting aspiring individuals to join us to create huge and meaningful impact to the medical industry in Asia.

What will I work on?

The candidate is a skilled engineer and works physics simulations, 3D volume image construction, signal processing, electromagnetic control with AI.

Our aim is to align you with the activities which truly interest you; will stretch you technically; help you grow and impact on millions of patients.

Who we love to see:

1. Strong mathematical skills - good foundations of linear algebra, matrix, differential algebra, statistics.

2. Strong physics skills - good knowledge of electromagnetism, finite element methods, and classical mechanics.

3. Strong problem solving and engineering skills.

4. Strong python, C++ or java coder

5. Good knowledge of python tools such as tensorflow, pytorch, numpy, pandas, sklearn, scipy, seaborn

6. Proficient in building deep learning neural network models

7. Optional: Published papers in top machine learning or computer vision conferences, ICML/NIPS/CVPR/ICCV

Education:

Degree in engineering or computer science or mathematics or physics

We can offer you:

Master, Teach, Learn - The opportunity to work with, learn from and share knowledge with ultra-smart colleagues in a culture of collaboration and technical excellence. We groom our employees and make sure that they stay at the cutting edge of the technology stack.

Impact - Huge potential to make a positive contribution across our business, people and partners

Remuneration – Competitive pay with share award for top performers.

We are also willing to groom engineers and fresh graduates who don't have a background in deep learning but are interested to learn. You will also have the opportunity to attend top machine learning conferences like NIPS and ICML.

Job Type: Full-time

Pay: $5, $8,000.00 per month

Work Location: In person

In this team you'll have a unique opportunity to have first-hand exposure to the strategy of the company in key security initiatives, especially in building scalable and robust, intelligent and privacy-safe, secure and product-friendly systems and solutions. Our challenges are not some regular day-to-day technical puzzles - You'll be part of a team that's developing novel solutions to first-seen challenges of a non-stop evolvement of a phenomenal product eco-system. The work needs to be fast, transferrable, while still down to the ground to making quick and solid differences.

Responsibilities:

l Build machine learning solutions to respond to and mitigate business risks in eHealthcare products/platforms. Such risks include and are not limited to abusive accounts, fake engagements, spammy redirection, scraping, fraud, etc.

l Improve modeling infrastructures, labels, features and algorithms towards robustness, automation and generalization, reduce modeling and operational load on risk adversaries and new product/risk ramping-ups.

l Uplevel risk machine learning excellence on privacy/compliance, interpretability, risk perception and analysis.

Qualifications:

l Master or above degree in CS, EE or other relevant, machine-learning-heavy majors.

l Solid engineering skills. Proficiency in at least two of: Linux, Hadoop, Hive, Spark, Storm.

l Strong machine learning background. Proficiency or publications in modern machine learning theories and applications such as deep neural nets, transfer/multi-task learning, reinforcement learning, time series or graph unsupervised learning.

l Ability to think critically, objectively, rationally. Reason and communicate in result-oriented, data-driven manner. High autonomy.

We're looking for a Machine Learning Engineer to join our dynamic AI/ML team. You'll build and enhance the intelligent systems and models that power our products. You'll work closely with data scientists, data engineers, and product teams to translate research prototypes into AI-powered solutions that drive business value.

• Build ML Models: Design, develop, and validate machine learning models for problems such as AI-driven predictive maintenance, operational optimization, and AI agents.

• Improve Models: Fine-tune models to make them more accurate and perform better.

• Work with Data: Collaborate with data engineers to get the right data ready for models and understand it well.

• Deploy Models: Help get models ready and put them into action so they can be used by our products or services.

• Monitor Performance: Keep an eye on how models are doing and fix any issues that come up.

• Research & Learn: Stay up-to-date with new ML techniques and find ways to apply them to our challenges.

• Collaborate: Work closely with other engineers, data scientists, and product managers.

Job Requirement:

• Experience: 5+ years of experience building and deploying machine learning models.

• Coding: Strong skills in Python and familiar with ML libraries like PyTorch, TensorFlow, or scikit-learn .

• ML Basics: Good understanding of common machine learning algorithms (e.g., regression, classification, clustering).

• Data Skills: Able to work with data, including cleaning and preparing it for models.

• Problem Solver: Great at breaking down complex problems and finding solutions using ML.

• Team Player: Good communication skills and enjoy working with a team.

In this team you'll have a unique opportunity to have first-hand exposure to the strategy of the company in key security initiatives, especially in building scalable and robust, intelligent and privacy-safe, secure and product-friendly systems and solutions. Our challenges are not some regular day-to-day technical puzzles -- You'll be part of a team that's developing novel solutions to first-seen challenges of a non-stop evolvement of a phenomenal product eco-system. The work needs to be fast, transferrable, while still down to the ground to making quick and solid differences.

Responsibilities:

l Build machine learning solutions to respond to and mitigate business risks in eHealthcare products/platforms. Such risks include and are not limited to abusive accounts, fake engagements, spammy redirection, scraping, fraud, etc.

l Improve modeling infrastructures, labels, features and algorithms towards robustness, automation and generalization, reduce modeling and operational load on risk adversaries and new product/risk ramping-ups.

l Uplevel risk machine learning excellence on privacy/compliance, interpretability, risk perception and analysis.

Qualifications:

l Master or above degree in CS, EE or other relevant, machine-learning-heavy majors.

l Solid engineering skills. Proficiency in at least two of: Linux, Hadoop, Hive, Spark, Storm.

l Strong machine learning background. Proficiency or publications in modern machine learning theories and applications such as deep neural nets, transfer/multi-task learning, reinforcement learning, time series or graph unsupervised learning.

l Ability to think critically, objectively, rationally. Reason and communicate in result-oriented, data-driven manner. High autonomy.