1,264 AI Development jobs in Singapore

Overview
MINDS has been caring for Persons with Intellectual Disabilities (PWIDs) and their families since 1962.
Grounded in the belief that all PWIDs have innate abilities and talents, MINDS is committed to empowering them and enhancing their quality of life, while advocating for greater inclusivity for PWIDs as a nation.
MINDS is today one of the largest charities in Singapore employing more than 850 staff. With the key focus to expand community-based services, improving the employability of PWIDs, strengthening education, and engendering inclusive community living, MINDS offers a holistic range of services and programmes across the PWIDs' lifespan.
These include schools, employment and training development centres, home-based care services and community-based services to cater to the physical, psychological, environmental and social needs of PWIDs. For more information, please visit
Responsibilities
This position is a technology leader responsible for driving execution and delivery of data, analytics, and AI initiatives in alignment with MINDSG Ltd's Vision and Mission. The deputy director will lead delivery and execution efforts across IT infrastructure, enterprise systems (including NetSuite and SAP), data analytics and artificial intelligence. This role ensures the execution of the set technological initiatives to improve organisational effectiveness and deliver better outcomes for clients, caregivers, volunteers, donors and staff.
Strategic Technology Leadership
Support the development of a future-forward technology roadmap prioritizing key initiatives
Advise on emerging technologies, risks, and digital opportunities to improve client experience, service delivery, and operational efficiency.
Collaborate with Heads of Departments, Centers, and Corporate Services to roll out technology initiatives
Lead digital transformation initiatives, including system integration
Enterprise Systems & Applications
Directly lead the implementation, optimisation, continuous improvement, and integration of enterprise resource planning (ERP) systems, including NetSuite and/or SAP.
Drive execution of projects to be delivered on time, within budget, and with measurable outcomes that support the organisation's strategic objectives.
Drive deployment of ERP-related initiatives to finance, HR, and service teams to ensure system usability and productivity improvement.
Data, AI & Automation
Support development and execute a data strategy, including data governance, architecture, quality, and accessibility across departments.
Directly drive the execution of the development and adoption of:
Data integration, master data management (MDM), advanced data analytics, and data development practices.
Generative AI-related initiatives to ensure ethical use, enhance knowledge management, client communication, and productivity
Robotic Process Automation (RPA) to streamline repetitive processes such as reporting, compliance tracking, and client administration.
IT Operations & Security
Manage and ensure initiatives/ projects meets IT policies, cybersecurity strategies, and disaster recovery plans stays updated and relevant.
Maintain business continuity and disaster recovery protocols in relation to data development and AI
Ensure compliance with regulatory requirements including PDPA, IMDA standards, and data ethics.
Digital Inclusion & Innovation
Support promotion of digital equity by collaborating with frontline teams to design inclusive, accessible digital solutions.
Drive test and scale tech pilots in collaboration with programme teams and external partners.
Evaluate and select emerging technologies and service partners to enhance service access and outcomes.
Leadership & Capacity Building
Hands-on leader and capable of building, leading, and developing a high-performing technology delivery team
Able to effectively communicate and engage organization-wide stakeholders to build digital literacy
Foster a culture of continuous learning and ethical innovation.
Stakeholder Engagement & Partnerships
Collaborate with sector peers and start-ups to co-develop scalable social impact solutions.
Manage external vendors, consultants, and technology partners to support delivery where necessary.
Build strong working relationships with internal stakeholders to ensure alignment and smooth execution of projects.
Support partnership with funders, tech vendors, and institutions to co-create solutions and secure technology grants.
Qualifications
Bachelor's degree in Information Systems, Computer Science, Engineering, or related field.
Other Information
At least 8 years of technology delivery and project management experience
Proven delivery experience with ERP systems (NetSuite and/or SAP will be a plus)
Strong hands-on experience with the delivery of data engineering, cloud platforms, data analytics platforms, integration platforms/middleware, and AI
Execution-driven with a strong bias for action and results. Pragmatic problem-solver who can adapt solutions to real-world social service contexts.
Innovative, excellent analytical and critical thinking skills with a high attention to detail.
Good communication and interpersonal skills in engaging and working in a multi teams environment
Strong understanding of best technology practices and business processes.
Passion for using technology to create social impact
Knowledge of ERP integrations and automation tools.
Experience with BI tools, SQL, Python, Power Platform, UiPath, or OpenAI APIs.
Experience in social service, healthcare, or government sectors.
Experience working in a technology consulting environment.
Certifications such as PMP, ITIL, SAP, NetSuite Administrator/Professional, etc.
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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.

Position Overview:

Black Sesame Technologies is a rapidly expanding artificial intelligence company backed by substantial VC funding, dedicated to pioneering algorithms and chips for artificial intelligence and image processing. As a Research Scientist in this role, you will collaborate closely with leading researchers to forge cutting-edge perception algorithms aimed at tackling real-world challenges in autonomous driving and beyond. The primary focus of perception is to identify and comprehend the surrounding environment of autonomous vehicles, supporting L2 and L3 automated driving capabilities. This involves constructing a real-time virtual representation of the local environment by processing input data predominantly from cameras, alongside data from complementary sensors such as radars, IMU, and ultrasonic sensors.

Job Description:

• Develop deep learning-based perception algorithms encompassing object detection, lane detection, segmentation, depth estimation, and other related tasks.
• Innovate state-of-the-art network architectures and training methodologies, assessing their efficacy in addressing vision-related challenges.
• Execute deep network compression tailored for ASIC platforms.
• Stay abreast of the latest advancements in deep learning and computer vision literature, proactively proposing novel concepts.
• Contribute to patent and research paper publications.

Job Requirements:

- Master Degree/ PhD in Computer Science, electrical engineering, or a related field.

- Possess 3+ years of experience in computer vision / machine learning development.

- Demonstrated expertise in research and development within one or more of the following domains:

• Deep network development, particularly with visual data.
• Object detection and tracking.
• Stereo / optical flow / depth estimation.
• Multi-view geometry and 3D computer vision.
• Structure from motion.
• Network compression and optimization.
• Network-based sensor fusion.
• Mathematical optimization.
• Proficient programming skills in Python (knowledge of C++ is advantageous).

Senior Solution Architect - AI Development
Get AI-powered advice on this job and more exclusive features.
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.
What You’ll Be Doing
Drive the implementation and deployment of NVIDIA Inference Microservice (NIM) solutions
Apply NVIDIA NIM Factory Pipeline to package optimized models (including LLM, VLM, Retriever, CV, OCR, etc.) into containers, providing standardized API access for on-prem or cloud deployment
Refine NIM tools for the community, aiding them in building high-performing NIMs
Build and implement agentic AI tailored to customer business scenarios using NIMs
Deliver technical projects, demos, and client support tasks as directed by the Solution Architecture Leadership
Provide technical support and mentorship to customers, facilitating the adoption and implementation of NVIDIA technologies and products
Collaborate with multi-functional teams to develop and broaden our AI solutions portfolio
Be an internal advocate for NVIDIA software and total solutions within the technical community
Position yourself as an inspiring leader in the industry by incorporating NVIDIA technology, especially inference services, into LHA, business partners, and the broader community and Assist in supporting the NVAIE team and driving NVAIE business in China
What We Need To See
7+ years of experience.
Bachelor's or equivalent experience in Computer Science, Artificial Intelligence, or a relevant field.
Proven experience in deploying and optimizing large language models. Proficiency in at least one inference framework (e.g., TensorRT, ONNX Runtime, PyTorch)
Strong programming skills in Python or C++. Familiarity with mainstream inference engines (e.g., vLLM, SGLang)
Experience with DevOps/MLOps, including Docker, Git, and CI/CD practices
Excellent problem-solving skills and the ability to solve complex technical issues
Proven ability to collaborate effectively across diverse, global teams, adapting communication styles while maintaining clear, constructive professional interactions
Experience in architectural build for field LLM project. Expertise in model optimization techniques, particularly using TensorRT
Knowledge of AI workflow development and implementation, and experience with cluster resource management tools. Familiarity with agile development methodologies
CUDA optimization experience and extensive experience in crafting and deploying large-scale HPC and enterprise computing systems
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Overview

Research Engineer (Software & AI Development) - HT1

Posting Start Date: 25/09/2025 • Schemes of Service: Research • Division: Engineering • Employment Type: Fixed Term

As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets that are relevant to industry demands while working on research projects in SIT. We are seeking a motivated Research Engineer to join our team in developing an AI Training Studio — an innovative platform for AI-vision-based quality inspection in manufacturing plants . The system will enable users to drag and drop foundational AI models to build customized AI pipelines for tasks such as image enhancement, detection, segmentation, and robotic control. You will contribute to both the backend development (pipeline orchestration, inference deployment) and the frontend interface (user-friendly drag-and-drop studio, similar to visual workflow tools). This role is ideal for an engineer eager to gain experience in building applied AI systems that bridge research and industrial deployment.

• Backend Development
  • Design and implement pipeline orchestration for drag-and-drop AI model workflows.
  • Integrate foundational models (classification, detection, segmentation, enhancement) into modular pipelines.
  • Build APIs to manage model training, deployment, and inference.
  • Automate the process of pushing trained models into an inference engine.
• Frontend Development
  • Develop an intuitive drag-and-drop web interface for building AI pipelines (similar to the attached prototype).
  • Enable users to configure model parameters, connect modules, and monitor training progress.
  • Display performance metrics (e.g., inference time, GPU utilization, throughput, ROI impact) in real time.
• System Integration
  • Work with the research team to connect AI pipelines to robotic control systems.
  • Support the deployment of trained pipelines in manufacturing testbeds.

• Have relevant competence in the areas of software and AI development.
• Have a degree in IT or Engineering.
• Experience in AI and any programming language will be advantageous.

Not applicable: Seniority level

Contract employment type

Job function: Engineering and Information Technology • Industries: Higher Education

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Organisation/Company SINGAPORE INSTITUTE OF TECHNOLOGY (SIT) Research Field Computer science Researcher Profile Recognised Researcher (R2) First Stage Researcher (R1) Country Singapore Application Deadline 25 Oct 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets that are relevant to industry demands while working on research projects in SIT.

We are seeking a motivatedResearch Engineer to join our team in developing anAI Training Studio — an innovative platform forAI-vision-based quality inspection in manufacturing plants . The system will enable users todrag and drop foundational AI models to build customized AI pipelines for tasks such as image enhancement, detection, segmentation, and robotic control.

You will contribute to both thebackend development (pipeline orchestration, inference deployment) and thefrontend interface (user-friendly drag-and-drop studio, similar to visual workflow tools). This role is ideal for an engineer eager to gain experience in building applied AI systems that bridge research and industrial deployment.

Key Responsibilities

• Design and implement pipeline orchestration for drag-and-drop AI model workflows.
• Build APIs to manage model training, deployment, and inference.
• Automate the process of pushing trained models into an inference engine.
• Frontend Development
  • Develop an intuitive drag-and-drop web interface for building AI pipelines (similar to the attached prototype).
  • Enable users to configure model parameters, connect modules, and monitor training progress.
  • Display performance metrics (e.g., inference time, GPU utilization, throughput, ROI impact) in real time.
• System Integration
  • Work with the research team to connect AI pipelines to robotic control systems.
  • Support the deployment of trained pipelines in manufacturing testbeds.

Job Requirements

• Have relevant competence in the areas of software and AI development.
• Have a degree in IT or Engineering.
• Experience in AI and any programming language will be advantageous.

Overview
Research Engineer (Software & AI Development) - HT1
Posting Start Date: 25/09/2025 • Schemes of Service: Research • Division: Engineering • Employment Type: Fixed Term
As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets that are relevant to industry demands while working on research projects in SIT. We are seeking a motivated
Research Engineer
to join our team in developing an
AI Training Studio
— an innovative platform for
AI-vision-based quality inspection in manufacturing plants . The system will enable users to
drag and drop foundational AI models
to build customized AI pipelines for tasks such as image enhancement, detection, segmentation, and robotic control. You will contribute to both the
backend development
(pipeline orchestration, inference deployment) and the
frontend interface
(user-friendly drag-and-drop studio, similar to visual workflow tools). This role is ideal for an engineer eager to gain experience in building applied AI systems that bridge research and industrial deployment.
Responsibilities
Backend Development
Design and implement pipeline orchestration for drag-and-drop AI model workflows.
Integrate foundational models (classification, detection, segmentation, enhancement) into modular pipelines.
Build APIs to manage model training, deployment, and inference.
Automate the process of pushing trained models into an inference engine.
Frontend Development
Develop an intuitive drag-and-drop web interface for building AI pipelines (similar to the attached prototype).
Enable users to configure model parameters, connect modules, and monitor training progress.
Display performance metrics (e.g., inference time, GPU utilization, throughput, ROI impact) in real time.
System Integration
Work with the research team to connect AI pipelines to robotic control systems.
Support the deployment of trained pipelines in manufacturing testbeds.
Qualifications
Have relevant competence in the areas of software and AI development.
Have a degree in IT or Engineering.
Experience in AI and any programming language will be advantageous.
Not applicable: Seniority level
Contract employment type
Job function: Engineering and Information Technology • Industries: Higher Education
Referrals increase your chances of interviewing at Singapore Institute of Technology by 2x
Get notified about new Research Engineer jobs in
Singapore, Singapore .
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Organisation/Company SINGAPORE INSTITUTE OF TECHNOLOGY (SIT) Research Field Computer science Researcher Profile Recognised Researcher (R2) First Stage Researcher (R1) Country Singapore Application Deadline 25 Oct 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No
Offer Description
As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets that are relevant to industry demands while working on research projects in SIT.
We are seeking a motivated Research Engineer to join our team in developing an AI Training Studio — an innovative platform for AI-vision-based quality inspection in manufacturing plants . The system will enable users to drag and drop foundational AI models to build customized AI pipelines for tasks such as image enhancement, detection, segmentation, and robotic control.
You will contribute to both the backend development (pipeline orchestration, inference deployment) and the frontend interface (user-friendly drag-and-drop studio, similar to visual workflow tools). This role is ideal for an engineer eager to gain experience in building applied AI systems that bridge research and industrial deployment.
Key Responsibilities
Design and implement pipeline orchestration for drag-and-drop AI model workflows.
Build APIs to manage model training, deployment, and inference.
Automate the process of pushing trained models into an inference engine.
Frontend Development
Develop an intuitive drag-and-drop web interface for building AI pipelines (similar to the attached prototype).
Enable users to configure model parameters, connect modules, and monitor training progress.
Display performance metrics (e.g., inference time, GPU utilization, throughput, ROI impact) in real time.
System Integration
Work with the research team to connect AI pipelines to robotic control systems.
Support the deployment of trained pipelines in manufacturing testbeds.
Job Requirements
Have relevant competence in the areas of software and AI development.
Have a degree in IT or Engineering.
Experience in AI and any programming language will be advantageous.
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(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.