502 AI Models jobs in Singapore

This role is part of pioneering algorithms and chips for artificial intelligence and image processing.

The primary focus of perception is to identify and comprehend the surrounding environment of autonomous vehicles, supporting L2 and L3 automated driving capabilities.

We are developing 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.

We execute deep network compression tailored for ASIC platforms.

Staying up-to-date with the latest advancements in deep learning and computer vision literature, we proactively propose novel concepts.

Our contributions include patent and research paper publications.

To be considered for this position, you must have a Master Degree/ PhD in Computer Science, electrical engineering, or a related field, along with 3+ years of experience in computer vision / machine learning development.

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

LOCATION

EMPLOYMENT TYPE

Permanent

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

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

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.

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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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).

Together, we inspire creativity and bring joy - a mission we all believe in and aim towards achieving every day.

To us, every challenge, no matter how difficult, is an opportunity; to learn, to innovate, and to grow as one team.

AI Innovation Researcher: Building Multimodal Models

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.