851 Machine Learning Algorithms jobs in Singapore

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.

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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.

Overview
Working at Atlassian
Atlassians can choose where they work – whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity. Interviews and onboarding are conducted virtually, a part of being a distributed-first company.

At Atlassian, we're on a mission to unleash the potential of every team. As part of that mission, we're investing deeply in Generative AI — pioneering advanced modeling and rapid innovations that accelerate how teams work, discover, and create.

We're seeking a
Machine Learning Engineer (P40)
to join our new
GenAI Modeling & Innovation Forge
in Singapore. You'll work with a small, high-impact team focused on advanced GenAI modeling, rapid prototyping, and applied research—building the foundations of the next generation of AI-powered innovations across Atlassian.

Responsibilities
What You'll Do

Contribute to Advanced GenAI Models

• Implement and fine-tune LLMs and embeddings under guidance from senior engineers and scientists.
• Build retrieval-augmented generation (RAG) and hybrid retrieval pipelines.
• Apply modern frameworks and best practices to support team experiments and prototypes.

Prototype and Experiment

• Help build proof-of-concept systems for GenAI-powered assistants and agentic workflows.
• Run experiments, collect data, and iterate quickly to improve models and features.
• Contribute to evaluation pipelines for groundedness, quality, and reliability.

Collaborate and Learn

• Work closely with ML engineers, applied scientists, and product teams to deliver end-to-end prototypes.
• Learn and apply best practices in ML engineering, experimentation, and deployment.
• Share results and insights to help drive the Forge's mission of rapid innovation.

Qualifications
What We're Looking For

Experience

• 2–4 years in ML/AI engineering or applied ML roles.
• Hands-on experience with at least one area: LLMs, NLP, embeddings, search/retrieval, or ML pipelines.
• Exposure to building or deploying ML-powered features or prototypes.

Skills

• Proficiency with ML frameworks (PyTorch, TensorFlow, Hugging Face).
• Familiarity with modern GenAI tools (LangChain, LlamaIndex) and vector databases (Weaviate, Pinecone, FAISS).
• Solid coding skills in Python and ability to write clean, maintainable code.
• Curiosity, adaptability, and eagerness to learn in a fast-paced environment.

Education

• Bachelor's in Computer Science, Machine Learning, or related field—or equivalent practical experience.

Nice to Have

• Experience with data pipelines, backend engineering, or cloud platforms (AWS, GCP, Azure).
• Familiarity with search evaluation metrics (e.g., NDCG, ).
• Contributions to open-source ML/GenAI projects.
• Strong interest in applied research and rapid prototyping.

Why Join Us?

• Be part of the founding team of Atlassian's Singapore-based GenAI Modeling & Innovation Forge.
• Work on cutting-edge applied GenAI projects with global visibility and impact.
• Learn from experienced engineers and scientists while contributing to meaningful prototypes.
• Join a mission-driven, remote-first company where innovation and growth are celebrated.

Benefits & Perks
Atlassian offers a wide range of perks and benefits designed to support you, your family and to help you engage with your local community. Our offerings include health and wellbeing resources, paid volunteer days, and so much more. To learn more, visit

.
About Atlassian
At Atlassian, we're motivated by a common goal: to unleash the potential of every team. Our software products help teams all over the planet and our solutions are designed for all types of work. Team collaboration through our tools makes what may be impossible alone, possible together.

We believe that the unique contributions of all Atlassians create our success. To ensure that our products and culture continue to incorporate everyone's perspectives and experience, we never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines.

To provide you the best experience, we can support with accommodations or adjustments at any stage of the recruitment process. Simply inform our Recruitment team during your conversation with them.

To learn more about our culture and hiring process, visit

.

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

Morgan McKinley is looking for a skilled Machine Learning Engineer - Image Gen for a 12-months contract with our client in the tech industry.

As a Machine Learning Engineer within the ML Platform team, you will play a key role in the creation of our new compute layer using Ray. You will help drive the set-up of the infrastructure for Ray on Kubernetes and its integration with the company's  existing Data system.

Responsibilities:

• Develop and Deliver High-Quality AI Infrastructure: Collaborate with the Machine Learning Platform team to design and build infrastructure for distributed data processing and model training using Ray. Ensure reproducibility across Kubernetes clusters by leveraging GitOps for cloud infrastructure management.
• Enhance Observability for Ray: Build and integrate monitoring and alerting solutions within observability stack, which includes Datadog, Prometheus, and Grafana. Contribute to the development of runbooks and DevOps documentation.
• Facilitate Ray Adoption Among Data Scientists: Partner with the product team to promote the use of Ray and provide support for users running jobs on Ray clusters.

Qualifications:

• With 3+ years of experience in Machine Learning Engineering and Ray
• Expertise in ML-Ops and Distributed Computing: Strong knowledge of distributed computing frameworks for data processing. Experience with Ray is a plus, though familiarity with frameworks like Dask, Modin, Beam, Horovod, or Deepspeed is also appreciated.
• Proficiency in Python and ML Ecosystems: Solid experience in Python programming and associated machine learning tools.
• Kubernetes and GitOps Expertise: Deep understanding of developing and deploying systems on Kubernetes. Familiarity with GitOps tools like ArgoCD, along with knowledge of Helm and Kustomize, is preferred.
• Strong DevOps Background: Experience with Infrastructure as Code (IaC) tools like Terraform is desirable.

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Morgan McKinley Pte Ltd

Koh Boon Sien

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