2,403 AI Professionals jobs in Singapore

Position Summary
To accelerate the adoption of clinical sequencing, Illumina is recruiting a world-class Machine Learning Scientist and Software Engineer to work on the development of novel deep learning algorithms and production-ready software for deciphering the effects of genetic variants in the human genome.
Major aims include modeling the effects of genetic variants on gene function, transcriptional regulation, and diagnosis of pathogenic variants in patients with cancer or rare genetic diseases. A key objective is to develop robust, scalable software implementations of research results and publish these findings in peer-reviewed journals. This will improve the accuracy, throughput, and reproducibility of genome interpretation, thereby removing barriers to the clinical adoption of whole genome sequencing. In addition to strong analytical and software development skills, this position will require initiative, autonomy, and scientific collaboration.
Responsibilities
Contribute to the development of deep learning algorithms for interpreting human genetic data, supporting efforts to identify pathogenic genetic variants using information from clinical phenotypes, protein structures, and genomic data.
Implement, test, and document software modules under the guidance of senior team members, with a focus on reliability, scalability, and efficiency.
Support collaborations with internal and external partners by preparing datasets, running analyses, and contributing to project deliverables.
Assist in preparing research results for internal reports, presentations, and publications, and contribute to integrating methods into software products for the genetics community.
Note: Listed responsibilities are an essential, but not exhaustive, list of usual duties. Changes may occur due to business needs.
Preferred Requirements
Knowledge in deep learning, statistics, bioinformatics, and/or genomics.
Knowledge in full-stack software development and deployment of scientific software.
Familiarity with software development best practices, including version control (e.g., Git), testing frameworks, and CI/CD.
Strong communication skills.
Ability to work in a fast-paced, competitive environment, with a track record of delivering complex scientific projects and publications under tight timelines.
Preferred Experience/Education
BS or MS in computer science, bioinformatics, computational biology, or a related field.
Illumina is an equal opportunity employer committed to providing employment opportunities regardless of sex, race, creed, color, gender, religion, marital status, domestic partner status, age, national origin or ancestry, physical or mental disability, medical condition, sexual orientation, pregnancy, military or veteran status, citizenship status or genetic information. We conduct background checks on applicants whom a conditional offer has been made. The background check process and any decisions will be made in accordance with applicable laws. Illumina prohibits the use of generative AI in the application and interview process. If you require accommodation to complete the application or interview process, please contact
To learn more, visit: The position will be posted until a final candidate is selected or the requisition has a sufficient number of qualified applicants. This role is not eligible for visa sponsorship.
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Overview

Deep Learning Architect, Generative AI Innovation Center at Amazon Web Services (AWS). The GenAI Innovation Center helps AWS customers implement Generative AI solutions and realize transformational business opportunities. The team of strategists, scientists, engineers, and architects works with customers to build bespoke solutions that harness the power of generative AI, imagine and scope high-value use cases, navigate challenges, develop proofs-of-concept, and plan for scalable deployment. The GenAI Innovation Center also provides guidance on best practices for applying generative AI responsibly and cost efficiently. You will design and run experiments, research new algorithms, and explore ways to optimize risk, profitability, and customer experience. We seek top architects, system and software engineers capable of using ML, Generative AI, and related techniques to design, evangelize, implement, and fine-tune state-of-the-art solutions for complex problems.

• Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate generative AI solutions addressing real-world challenges
• Interact with customers directly to understand business problems, assist in implementing generative AI solutions, and guide adoption patterns and paths to production
• Create and deliver best-practice recommendations, tutorials, blog posts, sample code, and presentations for technical, business, and executive stakeholders
• Provide customer and market feedback to product and engineering teams to help define product direction

• Bachelor of Science in Computer Science or related technical field (or equivalent experience); 3+ years of experience designing, building, and/or operating cloud solutions in a production environment
• 2+ years hosting and deploying ML solutions (training, fine-tuning, and inference)
• 2+ years of hands-on experience with Python to build, train, and evaluate models
• 2+ years of technical client engagement experience

• Masters or PhD in computer science or related technical field
• Strong working knowledge of deep learning, machine learning, generative AI, and 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
• Experience building cloud solutions with AWS

We’re committed to an inclusive culture. If you have a disability and need workplace accommodation or adjustments during the application and hiring process, including support for the interview or onboarding, please visit for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Overview
Deep Learning Architect, Generative AI Innovation Center at Amazon Web Services (AWS). The GenAI Innovation Center helps AWS customers implement Generative AI solutions and realize transformational business opportunities. The team of strategists, scientists, engineers, and architects works with customers to build bespoke solutions that harness the power of generative AI, imagine and scope high-value use cases, navigate challenges, develop proofs-of-concept, and plan for scalable deployment. The GenAI Innovation Center also provides guidance on best practices for applying generative AI responsibly and cost efficiently. You will design and run experiments, research new algorithms, and explore ways to optimize risk, profitability, and customer experience. We seek top architects, system and software engineers capable of using ML, Generative AI, and related techniques to design, evangelize, implement, and fine-tune state-of-the-art solutions for complex problems.
Responsibilities
Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate generative AI solutions addressing real-world challenges
Interact with customers directly to understand business problems, assist in implementing generative AI solutions, and guide adoption patterns and paths to production
Create and deliver best-practice recommendations, tutorials, blog posts, sample code, and presentations for technical, business, and executive stakeholders
Provide customer and market feedback to product and engineering teams to help define product direction
Basic Qualifications
Bachelor of Science in Computer Science or related technical field (or equivalent experience); 3+ years of experience designing, building, and/or operating cloud solutions in a production environment
2+ years hosting and deploying ML solutions (training, fine-tuning, and inference)
2+ years of hands-on experience with Python to build, train, and evaluate models
2+ years of technical client engagement experience
Preferred Qualifications
Masters or PhD in computer science or related technical field
Strong working knowledge of deep learning, machine learning, generative AI, and 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
Experience building cloud solutions with AWS
We’re committed to an inclusive culture. If you have a disability and need workplace accommodation or adjustments during the application and hiring process, including support for the interview or onboarding, please visit for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
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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.

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.

Responsibilities:

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.

Requirements:

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.

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.