479 AI Models jobs in Singapore
AI Researcher - Generative Media Models
Posted today
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AI Researcher - Generative Media Models
We are looking for a skilled AI researcher to join our team working on state-of-the-art generative media models. The ideal candidate will have expertise in developing novel tools, infrastructure, and algorithms towards the end goal of solving and building Artificial General Intelligence.
Key Responsibilities:- Design, implement, and evaluate cutting-edge deep learning algorithms and data curation for multimodal generative AI.
- Develop solutions to fundamental questions in machine learning and AI.
- Rigorously test and report research findings and developments clearly and efficiently both internally and externally.
- PhD in Computer Science, Artificial Intelligence, Machine Learning, or equivalent practical experience.
- Relevant experience in deep learning research and development, particularly in generative AI.
- Expertise in software development with one or more programming languages (e.g., Python) and deep learning frameworks (e.g., Jax, TensorFlow, PyTorch).
- Demonstrated experience in large-scale training of multimodal generative models.
- A track record of research or engineering achievements.
This role offers opportunities to collaborate with experts from various disciplines, including deep learning, computer vision, language modeling, and advanced generative architectures. Our team is committed to ensuring that our advances in intelligence are developed ethically and provide broad benefits to humanity.
Contract - Artificial Intelligence Engineer [Generative AI / Large Language Models (LLM)] (1 year)
Posted 14 days ago
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Join to apply for the Contract - Artificial Intelligence Engineer (Generative AI / Large Language Models (LLM)) (1 year) role at Infineon Technologies
This is a 1-year contract position.
The AI Engineer will serve as a technical expert in Natural Language Processing (NLP) and Language Model Learning (LLM), focusing on Chatbot, RAG (Retrieval-Augmented Generation), and Agentic Systems.
The primary responsibilities include:
- Expertise in NLP, specializing in LLM RAG, Chatbot, and Agentic Systems. Keep up-to-date with latest advancements and incorporate them into workflows.
- Transform prototypes into production solutions, adhering to best practices for development and deployment.
- Support operations by troubleshooting, fixing bugs, and implementing change requests to meet user needs.
Qualifications:
- Master's or Bachelor's degree in Computer Science, Mathematics, Statistics, or related field.
Experience:
- Minimum 5 years in NLP/AI/ML, with at least 1 year focusing on LLM.
- Hands-on experience with LLM/Generative AI, Chatbot, RAG, or Agentic Systems, including designing and implementing AI solutions.
- Proficiency in Software Engineering & Development cycles (CI/CD), scripting in Python.
- Strong experience with AWS services related to RAG, agents, and chatbots.
- Knowledge of Kubernetes/OpenShift.
- API development experience using Python/FASTAPI.
Attributes:
- Motivated, organized, proactive.
- Team player with cross-cultural communication skills.
- Customer-focused and results-oriented.
This is a 1-year contract via a third-party payroll, with benefits according to the partner company.
At Infineon, we drive decarbonization and digitalization, creating innovative solutions for green energy, mobility, and IoT. We value diversity and inclusion, offering a respectful and equal opportunity environment.
Interested? Let your recruiter know if you need any accommodations for the interview process.
#J-18808-LjbffrContract - Artificial Intelligence Engineer [Generative AI / Large Language Models (LLM)] (1 year)
Posted today
Job Viewed
Job Description
Contract - Artificial Intelligence Engineer (Generative AI / Large Language Models (LLM)) (1 year)
Join to apply for the
Contract - Artificial Intelligence Engineer (Generative AI / Large Language Models (LLM)) (1 year)
role at
Infineon Technologies
This is a 1-year contract position.
The AI Engineer will serve as a technical expert in Natural Language Processing (NLP) and Language Model Learning (LLM), focusing on Chatbot, RAG (Retrieval-Augmented Generation), and Agentic Systems.
The primary responsibilities include:
Expertise in NLP, specializing in LLM RAG, Chatbot, and Agentic Systems. Keep up-to-date with latest advancements and incorporate them into workflows.
Transform prototypes into production solutions, adhering to best practices for development and deployment.
Support operations by troubleshooting, fixing bugs, and implementing change requests to meet user needs.
Qualifications:
Master's or Bachelor's degree in Computer Science, Mathematics, Statistics, or related field.
Experience:
Minimum 5 years in NLP/AI/ML, with at least 1 year focusing on LLM.
Hands-on experience with LLM/Generative AI, Chatbot, RAG, or Agentic Systems, including designing and implementing AI solutions.
Proficiency in Software Engineering & Development cycles (CI/CD), scripting in Python.
Strong experience with AWS services related to RAG, agents, and chatbots.
Knowledge of Kubernetes/OpenShift.
API development experience using Python/FASTAPI.
Attributes:
Motivated, organized, proactive.
Team player with cross-cultural communication skills.
Customer-focused and results-oriented.
This is a 1-year contract via a third-party payroll, with benefits according to the partner company.
At Infineon, we drive decarbonization and digitalization, creating innovative solutions for green energy, mobility, and IoT. We value diversity and inclusion, offering a respectful and equal opportunity environment.
Interested? Let your recruiter know if you need any accommodations for the interview process.
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Cutting-Edge AI Researcher - Large Language Models
Posted today
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Job Description
At TikTok, we strive to create an innovative work environment that encourages collaboration and creativity.
The mission of the Eng-AI Innovation Center is to explore cutting-edge artificial intelligence technologies, including large language models (LLMs), multi-modal LLMs, and more. This enables our platform to better understand user creations and enhance content discovery, recommendation, and protection against abuse and fraud.
Our team focuses on developing core technology for LLM code direction, continuously optimizing code comprehension, reasoning, and generation capabilities. We also aim to improve code performance, privacy compliance, and research efficiency in actual business production environments.
To achieve this, we require a researcher with exceptional problem-solving skills and passion for machine learning, especially in LLMs and generative AI. The ideal candidate will have a PhD degree, top-tier conference papers, and programming skills in C/C++ or Python.
Benefits include a diverse, inclusive workplace where employees are valued for their skills, experiences, and perspectives. Our platform connects people worldwide, and so does our workplace.
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3D DEEP LEARNING ENGINEER
Posted 23 days ago
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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
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.
- 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.
3D DEEP LEARNING ENGINEER
Posted today
Job Viewed
Job Description
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.
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Research Engineer – Deep Learning Computer Vision (NSH)
Posted today
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Job 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.
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:
- Develop, train, and optimise deep learning models for object detection, classification, and segmentation using real-world datasets.
- Design and implement software modules to integrate the models into a working system prototype.
- Perform data annotation.
- Conduct experiments, analyse results, and iterate models for improved accuracy and efficiency.
- Prepare project documentation, technical reports, and academic publications.
- Collaborate with industry partners and contribute to technology transfer efforts.
Job Requirements:
- Possess strong technical knowledge and hands-on experience in:
- Deep learning frameworks (e.g., PyTorch, TensorFlow)
- Deep learning models (e.g., YOLO, U-Net, EfficientNet, ResNet, FPN, Fast R-CNN)
- Computer vision techniques and algorithms
- 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:
- Participation in Kaggle competitions, showcasing practical problem-solving and model development skills
- Model deployment (e.g., ONNX, TensorRT)
- Edge computing or embedded vision systems (e.g., NVIDIA Jetson Nano)
- Real-time processing and GPU acceleration
- 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
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AI Engineering Intern (Computer Vision & Deep Learning)
Posted 14 days ago
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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.
Deep Learning / AI Scientist - Liveness Detection and Biometrics
Posted 23 days ago
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Job Description
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:
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.
Design, train and deploy biometric models to correctly identify users
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
Stay updated with the latest research in biometrics, computer vision, and deep learning, incorporating new techniques to improve VIDA’s products
Collaborate with business, product, operations and engineering teams to deliver impact for our customers
Work independently or in a team to solve complex problem statements
Requirements:
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.
Deep understanding of modern computer vision techniques, deep learning and machine learning
Experience developing and deploying machine learning models in production
Experience with adversarial training to enhance model robustness
Proficient in Python, C++, Scala, or Java
Familiarity with modern deep learning frameworks such as TensorFlow, PyTorch, MXNet
Familiarity with cloud platforms like AWS, GCP, or Azure for model deployment.
Experience in on-device inference for machine learning models is a plus
Take pride in taking ownership and driving projects to have business impact
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.
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Deep Learning / AI Scientist - Liveness Detection and Biometrics
Posted today
Job Viewed
Job Description
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:
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.
Design, train and deploy biometric models to correctly identify users
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
Stay updated with the latest research in biometrics, computer vision, and deep learning, incorporating new techniques to improve VIDA’s products
Collaborate with business, product, operations and engineering teams to deliver impact for our customers
Work independently or in a team to solve complex problem statements
Requirements:
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.
Deep understanding of modern computer vision techniques, deep learning and machine learning
Experience developing and deploying machine learning models in production
Experience with adversarial training to enhance model robustness
Proficient in Python, C++, Scala, or Java
Familiarity with modern deep learning frameworks such as TensorFlow, PyTorch, MXNet
Familiarity with cloud platforms like AWS, GCP, or Azure for model deployment.
Experience in on-device inference for machine learning models is a plus
Take pride in taking ownership and driving projects to have business impact
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.
AtVIDA, 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.
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