810 AI Development jobs in Singapore

The ideal candidate will lead the adoption of cutting-edge AI technologies for cybersecurity purposes, with a focus on end-to-end development from model experimentation to production deployment.

• Develop innovative AI workflows and automation systems with human approval integration
• Design and manage real-time intelligence retrieval systems using vector search technology
• Deploy cloud-based AI services (AWS Sagemaker/Google Vertex AI)
• Implement CI/CD pipelines and containerized deployments (Docker/Kubernetes)
• Collaborate with cybersecurity experts to deliver impactful AI solutions

This role is ideal for engineers who enjoy applying AI to solve complex real-world challenges, particularly in the national security domain.

• Bachelor's Degree or higher in Computer Science, Data Science, or related field
• 2–3 years' hands-on experience in: Python, NLP, Computer Vision, Vector databases and CI/CD practices, LangChain and AI-powered applications
• Familiarity with data warehousing (Amazon Redshift, BigQuery) an advantage
• Strong problem-solving mindset and willingness to learn

We are seeking a highly skilled and experienced Artificial Intelligence Software Developer to join our team. This position will involve working on various projects, including multi-agent simulation platforms, collaborative research projects, and software development.

Main Responsibilities:

• Developing and maintaining the core of a multi-agent simulation platform in cooperation with other entities.
• Contributing to modeling the physics part of the simulator and driving further developments and/or configuring parameters for each model.
• Participating in project reviews, helping to resolve issues, avoiding misunderstandings between parties, and ensuring close technical follow-up of local R&D activities.
• Contribute to final R&D outcomes and deliverables.

Required Skills and Qualifications:

• Proficiency in C/C++/C# and experience with gRPC and protobuf.
• Experience with robotics simulation frameworks such as ROS2/Gazebo.
• Good knowledge of physics simulators and fluid dynamics.
• Knowledge of path planning algorithms (such as A*, D*, etc).
• Experience in ML/DRL implementations.
• Software developments knowledge about REST API and frontend frameworks.
• Proficient in Python/Docker/SQL.

Benefits:

This role offers an excellent opportunity to work on cutting-edge projects and contribute to the development of innovative solutions. If you are passionate about AI and software development and have the required skills and qualifications, we encourage you to apply.

The role of an AI Engineer Intern at a leading organization involves assisting in the development, testing, and deployment of AI models and tools to support projects.

• Develop, test, and refine AI models for data processing, content generation, and automation tasks.
• Maintain scripts for data collection, cleaning, and preparation.
• Support the integration of AI models into operational workflows and pipelines.
• Conduct research on AI tools and technologies to support ongoing initiatives.
• Collaborate with the team to improve model outputs and systems.
• Document technical work clearly for team reference and knowledge sharing.

• Current student or recent graduate in Computer Science, Data Science, Engineering, or a related field.
• Eagerness to learn, experiment, and take ownership of tasks.
• Good problem-solving skills and attention to detail.
• Ability to work independently while communicating progress clearly.

• Practical hands-on experience building and testing AI systems in a real-world environment.
• Mentorship from experienced AI engineers and strategists within a high-performance team.
• Opportunities to work on projects that will be deployed internally or for clients.
• Exposure to structured problem-solving, clear system design, and AI implementation practices.

As an AI Development Specialist, you will play a key role in shaping the future of marketing and operational efficiency through innovative AI solutions.

Job Description:

Support the development and deployment of AI tools tailored to meet business needs. Collaborate with cross-functional teams to identify opportunities for AI-driven growth and improvement.

Key Responsibilities:

• Design and implement AI workflows using platforms such as Zapier, ChatGPT, RPA tools, or LangChain.
• Develop and apply natural language processing (NLP) and prompt engineering techniques to enhance automated response quality.
• Evaluate and fine-tune pre-trained models for customer interaction and internal task support.
• Monitor AI performance and user feedback, providing actionable insights for improvement.
• Stay updated on generative AI trends and recommend tools or methods that could enhance business efficiency.

Required Skills and Qualifications:

• Pursuing or recently graduated with a degree in Computer Science, Information Systems, Engineering, AI, or related fields.
• Basic experience or strong interest in machine learning, NLP, or AI tool development.
• Proficient in Python (bonus if familiar with libraries like LangChain, spaCy, or OpenAI API).
• Strong curiosity about generative AI and its business applications.
• A strong command of both written and spoken English is beneficial due to the global nature of our industry.
• Familiarity with no-code/low-code platforms and API integration is a plus.
• Analytical and proactive with a problem-solving mindset.
• Comfortable working in a fast-paced, interdisciplinary team environment.

Benefits:

Join a dynamic and collaborative team where you can grow your skills and make a meaningful impact on business operations.

Others:

Apply now and take the first step towards a rewarding career in AI development!

Implement AI models for 3D data generation using deep learning techniques. Strong experience in 3D computer vision and 3D graphics required. Responsibilities include data preprocessing and feature engineering. Expert in GANs (Generative Adversarial Networks) and VAEs (Variational Autoencoders).

LOCATION

EMPLOYMENT TYPE

Permanent

1. Developing and implementing deep learning models for 3D data, such as point clouds, voxel grids, and triangle meshes.
2. Training and fine-tuning deep learning models on large datasets of 3D data, such as 3D scans of real-world objects and environments.
3. Using deep learning to extract features and representations from 3D data, such as object segmentation, surface normal estimation, and 3D object recognition.
4. Researching and implementing new techniques for 3D deep learning, such as point cloud convolutional neural networks and volumetric convolutional neural networks.
5. Collaborating with other engineers and researchers to integrate 3D deep learning models into other systems, such as robotics and autonomous vehicles.
6. Building and deploying 3D deep learning models on various platforms, including cloud, edge, and mobile devices.
7. Optimizing the performance of 3D deep learning models, including reducing memory and computational requirements and improving inference speed.
8. Communicating the results of their research and development activities to stakeholders and customers, including technical and non-technical audiences.
9. Keeping up with current research and developments in the field of 3D deep learning and identifying new opportunities for applying 3D deep learning to real-world problems.
10. Utilizing NVIDIA's deep learning frameworks, such as CUDA, cuDNN, and TensorRT, to optimize the performance of 3D deep learning models.
11. Using NVIDIA's Jetson platform for deploying deep learning models on edge devices.
12. Using NVIDIA's GPU-accelerated cloud platforms, such as NVIDIA GPU Cloud (NGC), for training and deploying deep learning models in the cloud.
13. Leveraging NVIDIA's AI-specific hardware, such as the NVIDIA A100 Tensor Core GPU, for faster and more efficient training and inference of deep learning models.
14. Utilizing NVIDIA's AI development tools, such as DeepStream and Isaac, to develop and deploy AI-powered applications for robotics and autonomous systems.
15. Using NVIDIA's Clara platform for medical imaging and other 3D data analysis.
16. Utilizing NVIDIA's Omniverse platform for creating and training models in virtual environments.

1. Strong technical skills: A 3D Deep Learning Engineer should have a solid understanding of deep learning and computer vision, as well as experience with programming languages such as Python and C++.
2. Experience with 3D data: You should have experience working with 3D data, such as point clouds, voxel grids, and triangle meshes, and should be familiar with the techniques and algorithms used for processing 3D data.
3. Experience with deep learning frameworks: You should have experience working with deep learning frameworks, such as TensorFlow, PyTorch, and NVIDIA's CUDA, cuDNN, and TensorRT, and should be familiar with the techniques used to optimize the performance of deep learning models.
4. Strong problem-solving skills: You should have strong problem-solving skills and be able to develop creative solutions to complex technical challenges.
5. Attention to detail: You should be meticulous and pay attention to detail, as small errors or bugs in the code can cause significant problems.
6. Strong communication skills: You should be able to effectively communicate technical ideas and solutions to both technical and non-technical audiences.
7. Flexibility and Adaptability: You should be able to adapt and learn quickly as the field of AI is constantly evolving and new techniques and technologies are emerging.
8. Creativity: You should have a creative mindset and be able to come up with new and innovative solutions to problems.
9. Team Player: You should have good collaboration skills and be able to work well in a team environment.
10. Passion for technology: You should have a genuine passion for technology and a desire to learn and stay current with the latest developments in the field.

Implement AI models for 3D data generation using deep learning techniques. Strong experience in 3D computer vision and 3D graphics required. Responsibilities include data preprocessing and feature engineering. Expert in GANs (Generative Adversarial Networks) and VAEs (Variational Autoencoders).

LOCATION

EMPLOYMENT TYPE

Permanent

What You’ll Do

• Developing and implementing deep learning models for 3D data, such as point clouds, voxel grids, and triangle meshes.
• Training and fine-tuning deep learning models on large datasets of 3D data, such as 3D scans of real-world objects and environments.
• Using deep learning to extract features and representations from 3D data, such as object segmentation, surface normal estimation, and 3D object recognition.
• Researching and implementing new techniques for 3D deep learning, such as point cloud convolutional neural networks and volumetric convolutional neural networks.
• Collaborating with other engineers and researchers to integrate 3D deep learning models into other systems, such as robotics and autonomous vehicles.
• Building and deploying 3D deep learning models on various platforms, including cloud, edge, and mobile devices.
• Optimizing the performance of 3D deep learning models, including reducing memory and computational requirements and improving inference speed.
• Communicating the results of their research and development activities to stakeholders and customers, including technical and non-technical audiences.
• Keeping up with current research and developments in the field of 3D deep learning and identifying new opportunities for applying 3D deep learning to real-world problems.
• Utilizing NVIDIA's deep learning frameworks, such as CUDA, cuDNN, and TensorRT, to optimize the performance of 3D deep learning models.
• Using NVIDIA's Jetson platform for deploying deep learning models on edge devices.
• Using NVIDIA's GPU-accelerated cloud platforms, such as NVIDIA GPU Cloud (NGC), for training and deploying deep learning models in the cloud.
• Leveraging NVIDIA's AI-specific hardware, such as the NVIDIA A100 Tensor Core GPU, for faster and more efficient training and inference of deep learning models.
• Utilizing NVIDIA's AI development tools, such as DeepStream and Isaac, to develop and deploy AI-powered applications for robotics and autonomous systems.
• Using NVIDIA's Clara platform for medical imaging and other 3D data analysis.
• Utilizing NVIDIA's Omniverse platform for creating and training models in virtual environments.

Who You Are

• Strong technical skills: A 3D Deep Learning Engineer should have a solid understanding of deep learning and computer vision, as well as experience with programming languages such as Python and C++.
• Experience with 3D data: You should have experience working with 3D data, such as point clouds, voxel grids, and triangle meshes, and should be familiar with the techniques and algorithms used for processing 3D data.
• Experience with deep learning frameworks: You should have experience working with deep learning frameworks, such as TensorFlow, PyTorch, and NVIDIA's CUDA, cuDNN, and TensorRT, and should be familiar with the techniques used to optimize the performance of deep learning models.
• Strong problem-solving skills: You should have strong problem-solving skills and be able to develop creative solutions to complex technical challenges.
• Attention to detail: You should be meticulous and pay attention to detail, as small errors or bugs in the code can cause significant problems.
• Strong communication skills: You should be able to effectively communicate technical ideas and solutions to both technical and non-technical audiences.
• Flexibility and Adaptability: You should be able to adapt and learn quickly as the field of AI is constantly evolving and new techniques and technologies are emerging.
• Creativity: You should have a creative mindset and be able to come up with new and innovative solutions to problems.
• Team Player: You should have good collaboration skills and be able to work well in a team environment.
• Passion for technology: You should have a genuine passion for technology and a desire to learn and stay current with the latest developments in the field.

Deep Learning Research Scientist

We are seeking a highly skilled and innovative Deep Learning Research Scientist to pioneer AI-driven approaches in drug discovery, leveraging unique datasets and cutting-edge technologies.

• Develop and train advanced deep learning models to transform the drug development process.
• Work with large multimodal datasets, including drug screening results, genomic data, and electronic health records.
• Contribute to the discovery of new antibiotics and the design of novel diagnostic tests.
• Collaborate with experts in biology and computer science to advance our research goals.
• Publish research findings in leading scientific journals.

• Bachelor's or Master's degree in Computer Science, Bioinformatics, or a related field.
• Proven experience in training large deep learning models using popular frameworks like TensorFlow or PyTorch.
• Familiarity with reinforcement learning, generative AI, or statistical modeling is a significant advantage.
• Experience working with large biological datasets or healthcare records is desirable, but a strong willingness to learn is equally valued.

Machine Learning, Cell Biology, Hospitals, Statistical Modeling, DNA, Treatment, Healthcare, Medicine, Career Development, Biology, Drug Discovery, Bioinformatics

The successful candidate will have the opportunity to work on cutting-edge projects, collaborate with world-renowned experts, and publish research findings in top-tier scientific journals. We offer a dynamic and supportive work environment, competitive salary, and opportunities for career growth and professional development.

Deep learning and AI are revolutionizing drug discovery, yet current models fall short of harnessing the vast diversity of biological data being generated. This project offers an opportunity to develop groundbreaking multimodal models for drug discovery and healthcare. By combining cutting-edge machine learning and generative AI approaches—spanning small molecule drug discovery, protein design, DNA and protein language models, genomic datasets, and electronic health records—we aim to create entirely new classes of AI foundation models that will revolutionize healthcare.

We are seeking a passionate and innovative Deep Learning Research Engineer to join our interdisciplinary team of biologists and computer scientists from MIT, NUS, and NTU. You will pioneer AI-driven approaches to accelerate the discovery of new drugs and diagnostics, leveraging unique datasets and state-of-the-art technologies.

• Train advanced deep learning models to transform drug discovery.
• Work with multimodal datasets, including drug screening results, genomic data, and electronic health records.
• Contribute to the discovery of new antibiotics and the design of novel diagnostic tests.
• Learn from and collaborate with experts in biology and computer science.
• Present research findings and publish in leading journals.

• Bsc or MSc in Computer Science, Bioinformatics, or a related field.
• Proven experience in training large deep learning models.
• Familiarity with reinforcement learning, generative AI, or statistical modeling is a plus.
• Experience with large biological datasets or healthcare records is desirable, but a strong willingness to learn is equally valued.

To apply, please visit our website at:

Interested applicants are invited to send in their full CV/resume, cover letter and list of three references (to include reference names and contact information). We regret that only shortlisted candidates will be notified.

At our organization, we're embarking on an exciting initiative to create a healthier and more sustainable future for everyone. Our goal is to not only improve people's lives but also the communities and environments we inhabit. This ambitious project aims to help a billion people live Healthier, Longer, Better Lives by 2030.

To achieve this vision, we need innovative individuals who are driven to make a meaningful impact. We're seeking talented professionals who are eager to work with and learn from exceptional leaders in their field.

As a Digital Transformation Specialist, you'll play a crucial role in championing and implementing digitalization and self-help capabilities at customer touch points. You'll support Technology, Digital, and Analytic (TDA) efforts to optimize processes and drive business process improvement for enhanced productivity and performance.

You'll be responsible for analyzing data to identify trends for automation, process improvement, and operational efficiency through Generative AI. Your key tasks will include:

• Supporting Head, Customer Experience in driving digital transformation and self-help tools at service touch points in Singapore and OSS Contact Centre with Compliance and Operational Risk in mind.
• Leveraging on Generative AI to design innovative solutions that streamline workflow and automate repetitive tasks.
• Developing and deploying machine learning models for predictive analytics, recommendation systems, and anomaly detection in various processes.
• Creating AI-based automation systems for business processes, customer service, data entry, and workflow optimization to enhance efficiency and productivity.
• Assisting with creating and updating documentation for AI models and processes, and supporting training sessions and workshops on AI tools and techniques.
• Monitoring and evaluating the performance of AI solutions, making necessary adjustments to optimize outcomes.

Key Requirements:

• Degree holder with knowledge of AI concepts. Understanding of artificial intelligence, machine learning, and deep learning principles.
• Proficiency in Retrieval-Augmented Generation (RAG) and Large Language Models (LLM).
• Data analytic: experience in generating and analyzing data effectively to identify key insights and trends.
• Designing customer journeys: designing