348 Senior AI Engineers jobs in Singapore

Skills required are -

Programming language : Python (Expertise in Pandas, NumPy)

Database knowledge : MS-SQL server, Mongo DB

Experience working on LLMs / RAG / Langchain

Experience on at least one of the cloud platforms : Azure / AWS / GCP

Hands-on experience with code deployment and source control tools such as Jenkins / Docker / Github

Hands-on expertise to design / develop / maintain ML / deep learning models

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.

Join to apply for the Deep Learning Engineer, TikTok e-Commerce role at TikTok

1 day ago Be among the first 25 applicants

Join to apply for the Deep Learning Engineer, TikTok e-Commerce role at TikTok

Responsibilities

TikTok will be prioritizing applicants who have a current right to work in Singapore, and do not require TikTok's sponsorship of a visa.

Responsibilities

TikTok will be prioritizing applicants who have a current right to work in Singapore, and do not require TikTok's sponsorship of a visa.

TikTok is the leading destination for short-form mobile video. Our mission is to inspire creativity and bring joy. TikTok has global offices including Los Angeles, New York, London, Paris, Berlin, Dubai, Singapore, Jakarta, Seoul and Tokyo.

Why Join Us

Creation is the core of TikTok's purpose. Our platform is built to help imaginations thrive. This is doubly true of the teams that make TikTok possible.

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. Status quo? Never. Courage? Always.

At TikTok, we create together and grow together. That's how we drive impact - for ourselves, our company, and the communities we serve.

Join us.

About The Team

The E-commerce Global Supply Chain and Logistics team is dedicated to enhancing clients' shopping experience and reducing logistics operational cost in TikTok E-commerce. We are currently looking for talented software engineers that have a deep understanding of machine learning (ML), operations research (OR), data mining and statistical inference. This position can be fulfilled in our Singapore offices.

Responsibilities

• Build deep learning and statistical models to provide end-to-end estimated time of arrival (ETA) prediction for the e-commerce logistics. Through fine adjustment of ETA expression to the consumers, improve the click-to-order rate while balancing the negative review indicators.
• Use data mining tools to build logistics network knowledge graphs, based on which to construct a situational awareness & early warning system for logistics fulfillment, enabling operations to discover and deal with logistics network anomalies, and to improve the logistics fulfillment quality together with logistics service providers.
• Analyze and predict the spatio-temporal trajectory sequence of express packages through deep learning, statistical inference and other algorithmic methods. This trajectory prediction can help to build a better understanding of logistics network dynamics, improve ETA prediction accuracy and provide important sample features for other prediction tasks.
• Build a service network design (SND) model for the location selection of transshipment centers and last mile stations based on an expected increase in logistics order volume.
• Collaborate with stakeholders to design and iterate strategies and models for predicting logistics events at the order level, including false shipments, user complaints, failed deliveries, false dispatching, negative reviews, and more.
• Drive the implementation of algorithmic models and ensure they generate tangible business value, such as logistics cost savings, GMV (Gross Merchandise Value) growth, and improved service levels.
• Develop innovative and state-of-the-art e-commerce logistics models and algorithms
• Support the production of scalable and optimised AI/machine learning (ML) models
• Focus on building algorithms for the extraction, transformation and loading of large volumes of realtime, unstructured data to deploy AI/ML solutions from theoretical data science models
• Run experiments to test the performance of deployed models, and identifies and resolves bugs that arise in the process
• Work in a team setting and apply knowledge in statistics, scripting and programming languages required by the firm
• Work with the relevant software platforms in which the models are deployed
  
  

• Master's or PhD degree in Computer Science, Engineering, Operations Research or related fields.
• Strong in data structures and algorithms, with excellent problem-solving ability and programming skills
• Experience in applied machine learning, familiar with one or more algorithms such as Matrix Factorization, Factorization Machines, Word2vec, Logistic Regression, Gradient Boosting Trees, Deep Neural Networks etc.
• Experience with at least one of the Big Data tools (For eg. Hive sql/Spark/Mapreduce; at least one of the Deep Learning tools(For eg. Tensorflow/Pytorch).
  
  

• Work experience in e-commerce, supply chain, logistics, transportation or related fields is preferred.
• Publications at KDD、NeurIPS、WWW、SIGIR、WSDM、CIKM、ICLR、ICML、IJCAI、AAAI and related conferences.
• Working experience in machine learning, operations research or big data analysis.
• Minimum of 1 year of relevant work experience, including but not limited to personalized recommendation/search, online advertising, natural language processing, supply chain management, or logistics optimization.
  
  

• Seniority level Entry level

• Employment type Full-time

• Job function Engineering and Information Technology
• Industries Entertainment Providers

Referrals increase your chances of interviewing at TikTok by 2x

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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:

• 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.

(Job ID: 105553)

Responsibilities:

• Design, develop, and optimize computer vision algorithms for defect detection, feature recognition, and automation in semiconductor manufacturing.
• Implement deep learning-based vision models for high-speed and high-accuracy inspection processes.
• Integrate vision systems with robotics, automation platforms, and semiconductor backend equipment (e.g., wire bonders, die bonders).
• Develop and fine-tune image processing techniques for pattern recognition, object tracking, and quality inspection.
• Work closely with cross-functional teams to enhance real-time vision inspection and improve production yield.
• Conduct data analysis, model validation, and performance tuning to meet industry standards.
• Optimize vision system performance in terms of latency, accuracy, and robustness.

Requirements:

• Strong experience in computer vision, image processing, and machine learning.
• Proficiency in Python, C++, OpenCV, TensorFlow, or PyTorch for vision-related applications.
• Experience with deep learning models (CNNs, GANs, Transformers) for vision tasks is an added advantage.
• Familiarity with semiconductor automation, optical inspection, or metrology is advantageous.
• Knowledge of real-time processing, embedded systems, and hardware acceleration (CUDA, FPGA, etc.) is an added advantage.

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EA Licence No.: 07C5771

EA Personnel Reg. No.: R24122504

EA Personnel Name: Edmund Ting Chao Siong

Let’s start with some numbers:

• H100 SXM: 504 (SuperPod)
• H100 PCI: 128
• A100 SMX: 120
• CPU: 600K cores
• 350pb SSD
• 33pb HDD

That is a lot of computing power, so why do we need it?

We’re pushing the boundaries of AI by building cutting-edge machine learning models and tools from the ground up. To support this, we’ve invested heavily in high-performance computing, including the Ahrefs Superpod, which boasts 60 nodes from 63 and scored 19.7 PFlops in Linpack, ranking it among the top 30 supercomputers in the world. Simply put, we have the infrastructure to turn ambitious ideas into reality.

For over a decade, Ahrefs has been crawling the web, processing petabytes of data, and delivering powerful insights through an intuitive interface. Now, we’re leveraging this expertise to develop innovative AI-driven solutions that help users navigate, analyze, and extract value from vast amounts of information like never before.

Let’s put that compute power to use!

In this role you’ll have the opportunity to work on cutting-edge research and turn it into real-world impact. We're looking for a dynamic Machine Learning Engineer to join us in creating cutting-edge AI products that push the boundaries of what’s possible. Bring your creativity, develop your own ideas, and see them through, from fuzzy concepts to production, all in a fast-moving, red-tape-free environment.

• Model Development
  • Work on LLMs and other AI models, spanning training, fine-tuning, inference optimization, and new architectures.
• Algorithm Research & Development
  • Design and implement algorithms for search, agents, knowledge retrieval, and generative AI applications.
• Stay on the Cutting Edge
  • Stay ahead of NLP and RL advancements, evaluate emerging models/frameworks (e.g., SSMs, text diffusion), and assess their impact on our products.
• Scaling & Optimization
  • Optimize model inference, reduce latency, and improve efficiency using techniques like distillation, quantization, and tensor parallelism.
• Collaborate with Engineering & Product Teams
  • Work closely with engineering and product teams to ship AI-driven features at scale.

• Experience with modern deep learning frameworks (e.g., PyTorch, JAX).
• Familiarity with transformer-based architectures and techniques (e.g. flash attention, speculative decoding, KV caching).
• Strong software engineering skills (Python, CUDA, or C++ a plus).
• Interest in one or more areas: large-scale training, agentic workflows, inference optimization, retrieval-augmented generation (RAG), reinforcement learning (RLHF/RL), or multimodal AI.
• Experience with distributed training and model deployment libraries (e.g. Megatron, Ray, Triton (both or either!), vLLM) is a bonus.

You’ll have opportunities to work on projects at the cutting edge of AI. You’ll get the chance to shape the future of our product and make a real impact.

If you're a Machine Learning Engineer with the drive to turn research into reality, we'd love to hear from you! Join us and be part of a team that's pushing the boundaries of technology and innovation.

That is a lot of computing power, so why do we need it?

We’re pushing the boundaries of AI by building cutting-edge machine learning models and tools from the ground up. To support this, we’ve invested heavily in high-performance computing, including the Ahrefs Superpod, which boasts 60 nodes from 63 and scored 19.7 PFlops in Linpack, ranking it among the top 30 supercomputers in the world. Simply put, we have the infrastructure to turn ambitious ideas into reality.

For over a decade, Ahrefs has been crawling the web, processing petabytes of data, and delivering powerful insights through an intuitive interface. Now, we’re leveraging this expertise to develop innovative AI-driven solutions that help users navigate, analyze, and extract value from vast amounts of information like never before.

Let’s put that compute power to use!

In this role you’ll have the opportunity to work on cutting-edge research and turn it into real-world impact. We're looking for a dynamic Machine Learning Engineer to join us in creating cutting-edge AI products that push the boundaries of what’s possible. Bring your creativity, develop your own ideas, and see them through, from fuzzy concepts to production, all in a fast-moving, red-tape-free environment.

• Work on LLMs and other AI models, spanning training, fine-tuning, inference optimization, and new architectures.
• Algorithm Research & Development
  • Design and implement algorithms for search, agents, knowledge retrieval, and generative AI applications.
• Stay on the Cutting Edge
  • Stay ahead of NLP and RL advancements, evaluate emerging models/frameworks (e.g., SSMs, text diffusion), and assess their impact on our products.
• Scaling & Optimization
  • Optimize model inference, reduce latency, and improve efficiency using techniques like distillation, quantization, and tensor parallelism.
• Collaborate with Engineering & Product Teams
  • Work closely with engineering and product teams to ship AI-driven features at scale.

• Experience with modern deep learning frameworks (e.g., PyTorch, JAX).
• Familiarity with transformer-based architectures and techniques (e.g. flash attention, speculative decoding, KV caching).
• Strong software engineering skills (Python, CUDA, or C++ a plus).
• Interest in one or more areas: large-scale training, agentic workflows, inference optimization, retrieval-augmented generation (RAG), reinforcement learning (RLHF/RL), or multimodal AI.
• Experience with distributed training and model deployment libraries (e.g. Megatron, Ray, Triton (both or either!), vLLM) is a bonus.

You’ll have opportunities to work on projects at the cutting edge of AI. You’ll get the chance to shape the future of our product and make a real impact.

If you're a Machine Learning Engineer with the drive to turn research into reality, we'd love to hear from you! Join us and be part of a team that's pushing the boundaries of technology and innovation.

Our data science team faces a big, exciting challenge: building machine learning models to improve the Fairsearch experience. What a user wants to see when they run a search, and what makes a piece of content better or more relevant than another – these are vital questions that inform how we rerank web pages. Sounds interesting? We'd love to hear from you.

Our motto is first do it, then do it right, then do it better.

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Direct message the job poster from Nicoll Curtin

Are you a Senior Machine Learning Engineer who wants to push the boundaries of computer vision and AI in real-world identity verification? Here's a chance to join a leading tech unicorn in the AI and digital identity space.

What you’ll do:

• Build and optimize computer vision models to improve performance in face recognition, liveness detection, and image quality assessments across diverse user populations.
• Work directly with product managers, annotation teams, and engineers to translate real-world identity verification needs into scalable model training and deployment strategies.
• Deep-dive into model performance issues to identify gaps, retrain models, and incorporate new data pipelines, including video and unstructured image data.
• Stay ahead of AI trends with research on new algorithms and contribute to full-cycle development, from dataset curation and labeling to model rollout.
• Contribute to product-level decisions with a strong understanding of how algorithms impact user security, fraud prevention, and product usability.

What we’re looking for:

• Solid background in Python, PyTorch, and computer vision, with experience handling large-scale image or video datasets.
• Hands-on experience training and evaluating ML models in real-world use cases — including accuracy tuning, fraud detection, and deployment into production environments.
• Effective communicator who can document, share insights, and align work with cross-functional teams.
• Comfortable working in a fast-paced, collaborative team that values innovation and ownership.

• Seniority level Mid-Senior level

• Employment type Full-time

• Job function Information Technology and Engineering
• Industries Software Development, Technology, Information and Media, and Financial Services

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We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.