440 Senior AI Engineers jobs in Singapore

We are seeking a talented and innovative individual to join our team as a Deep Learning Algorithm Specialist. In this role, you will have the opportunity to design and develop cutting-edge AI models that power TikTok's search engine.

You will be working on building a full-stack search engine system based on advanced AI and machine learning methods to provide a world-leading search experience. We value self-direction, intellectual curiosity, openness, and problem-solving, and we're looking for someone who shares these qualities.

• Final year or recent graduate with a background in Computer Science or a related technical field.
• Proficient coding skills and strong algorithmic and data structure knowledge using C++/Python/Java.
• Solid knowledge of machine learning and practical experience in applying it.

• Opportunity to work on real-world projects and make meaningful contributions to the company.
• Collaborative and dynamic work environment.
• Competitive compensation and benefits package.
• Access to cutting-edge technology and tools.

TikTok is a global community where creativity and joy come together. Our mission is to inspire people to express themselves authentically and connect with others. We're passionate about fostering an inclusive and diverse workplace culture that reflects the communities we serve.

Cynapse is a pioneering AI software company that specializes in developing cutting-edge Video Intelligence Solutions. Our innovative technology, powered by Generative AI, empowers organizations to enhance safety, operational efficiency, and security in complex environments.

Led by a global team with a proven track record of scaling startups into market leaders, we foster innovation, collaboration, and diverse perspectives. As a leading provider of video intelligence solutions worldwide, Cynapse serves clients globally and redefines what's possible with video analytics.

• This role offers an exciting opportunity to gain hands-on experience across the entire deep learning pipeline, including data preparation, model training, evaluation, and deployment.

• Work closely with engineers to design, build, and refine deep learning models for various Computer Vision tasks.
• Contribute to the optimization of models and pipelines by conducting experiments, analyzing results, and helping to improve model performance.
• Gain exposure to modern tools like Docker, CI/CD, and cloud platforms to support scalable, reliable model deployment.

• Currently pursuing or completed a Diploma/ Bachelor/ Master's in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related field.
• Basic understanding of machine learning concepts, demonstrated through the completion of at least one hands-on university or online module.
• Proficiency in Python programming (minimum 6 months of hands-on experience or equivalent AI/ML project experience, including GitHub contributions).
• Familiarity with at least one deep learning framework such as TensorFlow, PyTorch, or similar.

• Familiarity with building and optimizing ML pipelines, including data preprocessing, model training, testing, and deployment.
• Experience in software engineering practices like version control (Git), CI/CD pipelines, or Docker for containerization.
• Exposure to cloud platforms (AWS, GCP, Azure) for deploying and managing ML models in production.
• Knowledge of computer vision concepts and libraries (e.g., OpenCV).

Duration: Minimum 4 months internship duration, negotiable based on the candidate's schedule.

Artificial Intelligence Vision Expert

We seek a highly skilled Artificial Intelligence Vision Expert to join our team. The ideal candidate will possess in-depth knowledge of deep learning techniques, computer vision algorithms, and software development.

The successful candidate will be responsible for developing, training, and optimizing deep learning models for object detection, classification, and segmentation using real-world datasets.

They will also design and implement software modules to integrate the models into a working system prototype.

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.

The primary responsibility of this role is to support and contribute to an industry innovation research project. The Research Engineer will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and segmentation.

Key Responsibilities:

• Participate in and manage the research project together with the PI, Co-PI, and research team to ensure timely achievement of project deliverables.
• Undertake the following specific responsibilities in the project:

1. Develop, train, and optimise deep learning models for object detection, classification, and segmentation using real-world datasets.
2. Design and implement software modules to integrate the models into a working system prototype.
3. Perform data annotation.
4. Conduct experiments, analyse results, and iterate models for improved accuracy and efficiency.
5. Prepare project documentation, technical reports, and academic publications.
6. Collaborate with industry partners and contribute to technology transfer efforts.

Job Requirements:

• Possess strong technical knowledge and hands-on experience in:

1. Deep learning frameworks (e.g., PyTorch, TensorFlow)
2. Deep learning models (e.g., YOLO, U-Net, EfficientNet, ResNet, FPN, Fast R-CNN)
3. Computer vision techniques and algorithms
4. Python and relevant libraries (e.g., PyQt, OpenCV, NumPy, scikit-learn), particularly for developing Windows desktop application software incorporating deep learning models

• Hold at least a Bachelor's degree in Computer Science, Electrical/Electronic/Software Engineering, or a related field. A Master's or PhD degree in relevant areas will be advantageous.
• Familiarity with the following areas is advantageous:

1. Participation in Kaggle competitions, showcasing practical problem-solving and model development skills
2. Model deployment (e.g., ONNX, TensorRT)
3. Edge computing or embedded vision systems (e.g., NVIDIA Jetson Nano)
4. Real-time processing and GPU acceleration
5. Experience working on industry R&D project

Key Competencies:

• Able to build and maintain strong working relationships with team members, stakeholders, and external partners
• Self-motivated and committed to continuous learning and improvement
• Proficient in technical writing & presentation, research reporting, and academic publication
• Possess strong analytical, problem-solving, and critical thinking skills
• Demonstrate initiative and ownership in carrying out tasks independently

About Cynapse

Cynapse is a leading AI software company specializing in enterprise-grade Video Intelligence Solutions Powered by Generative AI, tailored to meet the unique challenges of various industries. Our vertical-specific solutions empower organizations to enhance safety, operational efficiency, and security in complex environments such as roads, seaports, airports, and cities. By combining advanced Vision AI with Generative AI, we continually push the boundaries of video analytics, delivering insights and automation that transform operations.

Led by a global team with a proven track record of scaling startups into market leaders, we foster innovation, collaboration, and diverse perspectives. Headquartered from US, Cynapse serves clients worldwide, redefining what's possible with video intelligence.

Job Description

We are looking for an AI Engineering Intern (Computer Vision & Deep Learning) to join our Computer Vision Model Engineering Team. This is a unique opportunity to contribute to the development and deployment of cutting-edge AI models by integrating deep learning, software engineering practices, and ML pipelines.

You'll work alongside a dynamic team, gaining hands-on experience and contributing to real-world AI projects that optimize the machine learning lifecycle.

As an AI Engineering Intern, you will:

• Gain hands-on experience across the entire deep learning pipeline, including data preparation, model training, evaluation, and deployment.
• Work closely with engineers to design, build, and refine deep learning models for various Computer Vision tasks, such as image classification, segmentation, object detection, action recognition, and more.
• Work with ML pipelines that support model deployment, assisting with tasks like model integration, data versioning , automated training, and testing.
• Contribute to the optimization of models and pipelines by conducting experiments, analyzing
• results, and helping to improve model performance.
• Gain exposure to modern tools like Docker, CI/CD , and cloud platforms to support scalable, reliable model deployment.
• Dive into cutting-edge research and gain insights into model architecture optimization, scalability, and challenges related to real-time application in Computer Vision.

Requirements:

• Currently pursuing or completed a Diploma/ Bachelor/ Master's in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related field.
• Basic understanding of machine learning concepts, demonstrated through the completion of at least one hands-on university or online module.
• Proficiency in Python programming (minimum 6 months of hands-on experience or equivalent AI/ML project experience, including GitHub contributions).
• Familiarity with at least one deep learning framework such as TensorFlow, PyTorch , or similar.
• Strong analytical thinking and problem-solving skills , with an emphasis on improving software pipelines .

Preferred (Bonus Skills):

• Familiarity with building and optimizing ML pipelines , including data preprocessing, model training, testing , and deployment .
• Experience in software engineering practices like version control (Git), CI/CD pipelines , or Docker for containerization.
• Exposure to cloud platforms (AWS, GCP, Azure) for deploying and managing ML models in production.
• Knowledge of computer vision concepts and libraries (e.g., OpenCV).
• Interest in exploring advanced topics like Generative AI, multi-modal learning , or real-time video analytics .

Duration:

• Internship duration: Minimum 4 months (negotiable based on the candidate's schedule).
• Availability: At least 4 days a week , with a preference for full-time commitment.
• Flexible start and end dates to accommodate exams or personal schedules.

Note : Due to the nature of the role, candidates must be based in Singapore or have relevant experience studying/working in Singapore.

Our mission is to create innovative, robust, and user-friendly digital identity solutions. We are looking for a passionate and skilled Deep Learning AI Scientist specializing in Liveness Detection and Biometrics to join our dynamic team. Your work will directly impact the security and reliability of VIDA's identity verification systems.

1. Liveness Detection Development: Design, train, and deploy advanced deep learning models to ensure robust liveness detection, preventing spoofing attacks using photos, videos, masks, or other methods.
2. Design, train and deploy biometric models to correctly identify users.
3. Own the full lifecycle of deploying models: from data labelling, working with engineers to design scalable APIs, to monitoring and A/B testing new model versions.
4. Stay updated with the latest research in biometrics, computer vision, and deep learning, incorporating new techniques to improve VIDA’s products.
5. Collaborate with business, product, operations and engineering teams to deliver impact for our customers.
6. Work independently or in a team to solve complex problem statements.

1. An advanced degree in a quantitative field, and 3+ years of hands-on experience in deep learning model development for biometrics or liveness detection or a similar field.
2. Deep understanding of modern computer vision techniques, deep learning and machine learning.
3. Experience developing and deploying machine learning models in production.
4. Experience with adversarial training to enhance model robustness.
5. Proficient in Python, C++, Scala, or Java.
6. Familiarity with modern deep learning frameworks such as TensorFlow, PyTorch, MXNet.
7. Familiarity with cloud platforms like AWS, GCP, or Azure for model deployment.
8. Experience in on-device inference for machine learning models is a plus.
9. Take pride in taking ownership and driving projects to have business impact.
10. Thrive in a fast moving collaborative environment.

What are we trying to solve?

We have 7.5 billion people on Earth, of which over 1 billion cannot securely prove their identity right now. Every year, 140 million babies are born, of which 40 million go unregistered. Simply put, these people are deprived of social benefits, such as education and health, their civil rights to vote and travel; and are excluded from the economy because they cannot sign up for bank accounts, loans, welfare programs etc. We believe this is unacceptable, and needs to change.

At VIDA , we are creating a frictionless digital identity system. One that fulfills the needs and expectations of our times, and is available anywhere, for everyone.

Why are we solving this problem?

The United Nations (UN) and World Bank ID4D initiatives aim to provide everyone on the planet with a legal identity by 2030. This deadline is just 9 years away, we are expecting a digital identity to be a legal human right by then and we at VIDA want to be pioneers in leading this change.

Who are we?

We are a highly driven bunch of people to solve this problem for our own reasons. Whether it is to solve for misleading doctors, or because we didn’t get access to fair ration due to corruption - Our collective goal aligns.

Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? The Generative AI Innovation Center helps AWS customers implement Generative AI solutions and realize transformational business opportunities. This is a team of strategists, scientists, engineers, and architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI. The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, define paths to navigate technical or business challenges, develop proof-of- concepts, and make plans for launching solutions at scale.

The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies.

You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.

We're looking for top architects, system and software engineers capable of using ML, Generative AI and other techniques to design, evangelize, implement and fine tune state-of-the- art solutions for never-before-solved problems.

As a Deep Learning Architect, you will

• Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate generative AI solutions to address real-world challenges
• Interact with customers directly to understand their business problems, aid them in implementation of generative AI solutions, brief customers and guide them on adoption patterns and paths to production
• Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder
• Provide customer and market feedback to product and engineering teams to help define product direction

About the team

Diverse Experiences

AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.

Why AWS?

Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture

Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (diversity) conferences, inspire us to never stop embracing our uniqueness.

Mentorship & Career Growth

We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud.

• Bachelor of Science degree in Computer Science, or related technical, math, or scientific field (or equivalent experience)
• 5+ years of experience in designing, building, and/or operating cloud solutions in a production environment
• 4+ years experience hosting and deploying ML solutions (e.g., for training, fine tuning, and inference)
• 4+ years of hands on experience with Python to build, train, and evaluate models
• 4+ years of technical client engagement experience

• Masters or PhD degree in computer science, or related technical, math, or scientific field
• 3+ years experience working with deep learning, machine learning, generative AI, or statistics
• Experience building generative AI applications on AWS using services such as Amazon Bedrock and Amazon SageMaker.
• Experience communicating across technical and non-technical audiences, including executive level stakeholders or clients
• Experience building cloud solutions with AWS

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.