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The batch #4 AI Apprenticeship Programme will end in 

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About AI Singapore's Talent Portal

AI Singapore’s Talent Portal aims to connect potential employers looking for AI talent to apprentices from the AI Apprenticeship Programme. Employers may post your AI-related job opportunities on this portal where interested apprentice(s) can apply directly. 

Please note that this is open to Singapore-based companies only. If you are representing a recruitment agency, please contact us at here.

Structure of the AI Apprenticeship Programme

Selection

All AI Apprentices have succeeded in a 3-stage evaluation process before they are accepted into the programme: Resume Screening, Technical Assessment and In-person Interview

The Programme

The programme comprises of 2 months deep-skilling curriculum focused on AI programming and deployment, followed by working on a 100E industry project for the remaining 7 months.​

Industry

At the end of the programme, the apprentices are certified as AI Engineers and will be fully equipped to design, build, train and deploy an AI model end to end.

AI Apprentices (Batch 4)

Side Projects

  • Reinforcement Learning for HVAC Power Consumption Optimisation using OpenAI's Gym and EnergyPlus
  • AI in Agriculture
  • AI-assisted Creativity - Lyrics Generation using LSTM in PyTorch

Skills/Libraries

Languages: Python(Intermediate), SQL(Basic), Arduino/C/C++(Basic)

A. Febriyan

Area of Interest: Recommendation Engine, Reinforcement Learning, Deep Learning, Embedded Electronics, Music Tech, Interactive Art, Sustainability
Background: B.Eng in Environmental Engineering (NUS)

Side Projects

  • Implementing ULMFiT methods to fine tune a pre-trained language model and classify texts
  • Utilising Hidden Markov Models to tag parts of speech

Skills/Libraries

Language: Python(Intermediate), R(Intermediate), SQL(Basic)

A. Yusof

Area of Interest: Recommendation Engine, Natural Language Processing, Unsupervised Learning, Computational Social Science
Background: B.SocSc in Political Science (SMU)

Side Projects

  • Object detection
  • Image classification

Skills/Libraries

Language: Python(Intermediate), SQL(Basic), Arduino/C/C++(Basic)

 

Libraries: Keras/Tensorflow, SKlearn, Matplotlib

Cheng Z.

Area of Interest: Deep Learning, Computer Vision, Robotic Process Automation, Data Engineering
Background: M.Sc in Business Information Technology (University of Central Lancashire)

Side Projects

  • GANs-driven Artist Suite
  • Food recommendation with knowledge graph

Skills/Libraries

Languages: Python (Intermediate), R (Intermediate), SQL (Intermediate), C++ (Basic), Java (Basic), MatLab (Basic)


Libraries: Pandas, Dask, Scikit-Learn, Matplotlib, Seaborn, Networkx, PyTorch, TensorFlow/Keras, Requests, BeautifulSoup, Pillow, IPython

M. Choo

Area of Interest: AutoML, Computational Creativity, Computer Vision, Cryptography & Security, Explainable AI, Natural Language Processing, Federated Learning, Reinforcement Learning
Background: B.Sc in Computational Biology (NUS)

Side Projects

  • Question - Answering for Bible Commentaries
  • Macro Capital allocation framework for neural nets

Skills/Libraries

Languages: Python, SAS, SQL, Tableau

 

Libraries: Statsmodels, TensorFlow, Tensorflow-Hub, PyTorch, BeautifulSoup, Selenium, Plotly, Dash, Seaborn, Pandas, sklearn

J. Tan

Area of Interest: Time Series Analysis and Forecasting Machine Learning for Financial Trading, NLP - Document Embeddings, Information Retrieval
Background: B.A in Economics (NUS)

Side Projects

  • Image captioning for sorting photos
  • Reinforcement learning for agriculture

Skills/Libraries

Languages: Python(Intermediate), SQL(Basic), Arduino/C/C++(Basic)

Kew W. M.

Area of Interest: Deep learning, Reinforcement learning, Federated learning, AI ethics, Environmental sustainability, Physics
Background: B.Sc in Physics (NUS)

Side Projects

  • Automated understanding of complex Q&A content

Skills/Libraries

Languages: Python(Intermediate), SQL(Basic), JavaScript(Basic), C++(Basic), MatLab(Basic)

 

Libraries: PyTorch, Tensorflow/Keras, Pandas, Numpy, Scikit-Learn, Matplotlib, Seaborn, OpenCV

Kow Y. S.

Area of Interest: Human Pose Estimation, Virtual Reality, Neural Network Architecturing, Multi-Task Learning
Background: B.Sc in Physics (NUS)

Side Projects

  • Customer Recommendation Engine using clustering and time series analysis
  • Reinforcement learning for agriculture

Skills/Libraries

Languages: Python (Intermediate), MATLAB (Basic), SQL (Basic), C (Basic)

 

Libraries: Pandas, Scikit-learn, Tensorflow, PyTorch, Flask

N. Lim

Area of Interest: Deep Learning, Statistical Learning, Federated Learning, Homomorphic Encryption, Cryptography & Security, AI Ethics
Background: B.Eng in Biomedical Engineering (NUS)

Side Projects

  • Various Award-Winning Hackathon MVPs (Chatbot, API, Web/Mobile App)

Skills/Libraries

Languages: Python, PHP, Java, SQL, HTML, CSS, JavaScript

 

Frameworks: TensorFlow, Flask, Laravel, Spring Boot, Android, Swift

Lim X. Y.

Area of Interest: Computer Vision, Deep Learning, Agile Methodology (Scrum), Design Innovation, Full-Stack Development
Background: B.Eng in Information and Communications Technology (Software Engineering) (SIT)

Side Projects

  • AI-Assisted Creativity
  • Poem Generation

Skills/Libraries

Languages: Python(Intermediate), R(Intermediate), MatLab(Basic)

M. Loke

Area of Interest: Deep Learning, Computer Vision, Transportation, Sustainability
Background: B.Eng in Engineering Systems and Design (SUTD)

Side Projects

  • Auto labeler Application for text and images
  • Emotion Recognition on Mobile device

Skills/Libraries

Languages: Python(Intermediate), SQL(Intermediate), R(Intermediate), MatLab(Basic)

 

Libraries: Pandas, Numpy, Scikit-Learn, Matplotlib, Seaborn, Plotly, Dash, Pillow, OpenCV, Scikit-Image, Tensorflow/Keras, PyTorch, BeautifulSoup, RShiny

Ng J. M.

Area of Interest: Deep Learning, Computer Vision, Natural Language Processing, Time Series, Meta Learning, Few Shot Learning, Zero Shot Learning
Background: B.Eng in Chemical Engineering (NUS)

Side Projects

  • Implementing AI on LEGO and Raspberry Pi robots
  • Facial keypoint detection and facial recognition
  • Image captioning

Skills/Libraries

Languages: Python (Intermediate), C++ (Basic), MATLAB (Basic)

 

Libraries: PyTorch, TensorFlow /Keras, OpenCV, Pandas, Scikit-Learn, ROS

Ng L. P.

Area of Interest: Deep Learning, Computer Vision, Signal Processing, Robotics, IoT, Predictive Maintenance
Background: B.Eng in Mechanical Engineering (NTU)

Side Projects

  • Image captioning for sorting photos

Skills/Libraries

Languages: Python, C++, C#, SQL, NodeJS
Skills: Backend Programming, 3D Programming, Machine Learning Programming

 

Libraries: Pandas, Scikit-learn, Tensorflow, PyTorch, Qt, Flask, .Net Core, Unity 3D, OpenCV

Sun Y.

Area of Interest: Deep Learning, Computer Vision, Human Pose/Activity Estimation, Software Architecture Design, Agile Methodology (Scrum), Full-Stack Development
Background: M.Sc in Design Pattern and Intelligent Control (Northwestern Polytechnical University)

Side Projects

  • GANs-driven Artist Suite
  • Food recommendation with knowledge graph

Skills/Libraries

Languages: Python, R, SQL

 

Libraries: Tableau

Tan K. C.

Area of Interest: Deep Learning, Federated Learning
Background: M.Tech in Enterprise Business Analytics (NUS)

Side Projects

  • Image captioning for sorting photos

Skills/Libraries

Languages: Python (Intermediate), SQL (Intermediate)

Libraries: Pandas, Sciki-Learn, Matplotlib, Seaborn, TensorFlow/Keras, PyTorch, BeautifulSoup

K. Wang

Area of Interest: Natural Language Processing - Topic Modeling, Information Retrieval, Predictive Analytics for Finance, Recommendation Engine, Computer Vision
Background: B.BA (NUS), CFA Level III

Side Projects

  • QA using BERT model
  • Travel planning assistant chatbot

Skills/Libraries

Languages: Python, SAS, SQL
Skills: AWS, Tableau

Libraries: Pytorch, TensorFlow/Keras, Pandas, Scikit-Learn

Weng J.

Area of Interest: Natural Language Processing, Embeddings in Deep Learning, Object Detection, AutoML
Background: M.Sc in Statistics (NUS)

Skills/Libraries

Languages: Python, Java, SQL, MatLab
Skills: Machine Learning

 

Libraries: Tensorflow, PyTorch, PyQt, Flask

Zeng Z. A.

Area of Interest: Machine Learning, Deep learning, Energy, Commodities
Background: B.Eng in Electrical & Electronics Engineering (NTU)

AI Apprentices (Batch 3)

K. CHONG

Area of Interest: Bioinformatics, Translational research, Computational Biology, Machine learning
Background: PhD in Interdisciplinary Studies, Microbiology (NTU)

F. LIM

Area of Interest: NLP, Statistical & Predictive Modeling
Background: B.Sc in Statistics, Minor in Economics (NUS)

S.X. GO

Area of Interest: NLP, Deep Learning, Reinforcement Learning
Background: M.Sc in Mathematics, B.Sc. in Applied Mathematics (NUS)

Q. HAN

Area of Interest: Cognitive Science, Human Machine Interface, Fraud Detection
Background: B.Eng in Electrical Engineering, BBA (NUS)

K.B. KOH

Area of Interest: Deep learning, deployment, Software Engineering
Background: B.Sc in Computer Science, M.Sc in Technology Management (NTU)

K. KOK

Area of Interest: Robotics, Deep Learning, Reinforcement Learning
Background: B.Sc in Information Systems, BBM Business Management (SMU)

B. LEE

Area of Interest: Natural language processing, Statistical Machine Learning
Background: B.Eng in Chemical Engineering, Second major in Statistics (NUS)

K. LEE

Area of Interest: NLP, Predictive Analytics, Customer Lifetime Value Modeling, Machine Learning
Background: B.Sc in Electrical Engineering (Texas A&M University), MBA (University of Hull)

X.J. LEE

Area of Interest: NLP, Deep Learning, Deep Unsupervised Learning
Background: B.Sc in Statistics & Actuarial Science, Minor in Computer Science (University of Toronto)

W.M. LEK

Area of Interest: TBC
Background: TBC

X.L. LIU

Area of Interest: Machine Learning, Computer Vision
Background: M.Tech in Knowledge Engineering (NUS)

M. ANTONIO

Area of Interest: NLP, Deep Learning, Big Data (Hadoop/Spark), Simulation, Healthcare
Background: M.Sc. in Analytics (Georgia Tech), M.Sc. in Industrial Chemistry (NUS)

W.X. NG

Area of Interest: Deep Learning, Data Engineering, Robotics, IoT
Background: B.Eng in Engineering Product Development (Electrical Engineering) (SUTD)

T.K. TAN

Area of Interest: Machine Learning, RPA
Background: B.Sc in Accounting and Finance (UOL), Postgraduate Diploma in Systems Analysis (NUS)

J.Y. TEO

Area of Interest: Software Engineering, NLP, Graph Analytics, Deep Learning
Background: B.A in Public Policy and Global Affairs, Minor in Computing and Data Analytics (NTU)

C.H. WONG

Area of Interest: NLP, Machine Learning, Deep Unsupervised Learning, Defence
Background: B.Eng in Chemical Engineering, University Scholars Program (NUS)

S.L. YAP

Area of Interest: Machine Learning, AI Application and Smart Device Development
Background: M.Sc Materials Science and Engineering (NUS)

Employers

Submit your job openings!

  • Please submit ONLY Artificial Intelligence (AI), Machine Learning, Data Science-related jobs openings.
  • We will only accept submissions from hiring companies. If you are representing a recruitment firm, please contact us at here

Fees

  • There is no fees involved.
  • The talent portal provides access to the AI Apprentices at no cost to all stakeholders in order to contribute to AI talent recruitment and the ecosystem.

Frequently Asked Questions

Most frequent questions and answers

Who can post a job opening?

We currently accept job postings from companies and government agencies in Singapore who are looking for AI/ML/Data Engineers and Scientists. If you are a recruitment firm or headhunter, please contact AI Singapore first!

Who are the apprentices?

The AI Apprentices are Singaporeans who are in the programme to deepen their AI/ML skills. The AI Apprenticeship Programme is  a deep-skilling programme. You can expect the AI Apprentices to be highly competent in designing, programming and building AI/ML models. 

Why can't I see my job posting?

AI Singapore curates all job posting, and only approved  job postings will be displayed within 3-5 business days. AI Singapore reserves the right to reject your submission.

Who can submit a resume?

We are supporting our AI Apprentices only. We will not be accepting applications from candidates outside of the AI Apprenticeship Programme.

Can I contact the apprentices directly without a job posting?

No. If an apprentice is interested in your job role, he or she will apply for it via this portal. You can then follow-up as per normal interview/hiring process.

What AI tools and frameworks would the apprentices know?

Most of the projects done by the apprentices would be built in Python and using frameworks such as Tensorflow/Keras, PyTorch. They would also have built their tools on platforms such as Microsoft Azure Cloud and Spark/Databricks.

Do I have to pay to submit a job listing?

There are no costs. Our goal for this portal is to help match industry to our AI Apprentices.

We need AI Scientist and not engineers!

Some of our AI Apprentices do hold Masters and/or PhDs in disciplines such as Engineering, Mathematics and Statistics. Upon completion of the AI Apprenticeship Programme, we would consider them as a junior AI/Data Scientist.

Stay in touch!

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