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AI Engineer Intern (Machine Learning)

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Onsite

AI Engineer Intern (Machine Learning)

MIKOMIKO PTE. LTD.

AI Engineer Intern (Machine Learning)

Skills

Google Cloud PlatformDeep LearningDockerPythonPyTorchTensorFlowRMachine LearningAIAWSKubernetes

1 month ago

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Important information


Contract type:

Permanent, Internship

Work mode:

Onsite

Published on:

17 September 2026

What they need


Date Listed

04 Sep 2026

Experience Level

Entry Level / Junior Executive, Experienced / Senior Executive

Profession

Sciences / Laboratory / R&D

Industry

Artificial Intelligence / Smart Automation

Job Period

Flexible Start, For At Least 3 Months

Location Name

85 Science Park Dr, Singapore Science Park 1, Singapore 118259, Singapore

Address

85 Science Park Dr, Singapore Science Park 1, Singapore 118259

Map

Company Profile

At Mikomiko, we are at the forefront of AI Technology and AI Solution development and deployment. Our expertise spans across machine learning, deep learning, multi-model learning, transformer, NLP, frontend, backend, cloud and embedded software development, to focus on AI Generated Content (AIGC) generation and beyond. Join us in shaping the future of AI and revolutionizing industries through innovation and advanced technology.

Job Description

We are looking for Machine Learning Engineers with a strong algorithmic foundation and solid model training experience.

You will be responsible for designing, training, and optimizing core models that power the AI systems behind Mikomiko. This role is ideal for engineers who pursue technical excellence, enjoy solving complex ML problems, and want to bring cutting-edge research into real-world applications.

  • Research, implement, and optimize machine learning and deep learning models;
  • Design and execute training, fine-tuning, and evaluation workflows for large-scale models;
  • Explore and improve upon Transformer, Diffusion, and Vision-Language architectures;
  • Build efficient data processing and training pipelines to support continuous iteration;
  • Track and experiment with state-of-the-art research and open-source frameworks;
  • Collaborate with product and engineering teams to integrate models into production environments.

Job Requirements:

  • Bachelor’s or higher degree in Computer Science, Artificial Intelligence, Mathematics, or related fields;
  • Strong theoretical foundation in machine learning, deep learning, and probability/statistics;
  • Proficient in Python and major ML frameworks (PyTorch / TensorFlow);
  • Hands-on experience in training, fine-tuning, and optimizing models;
  • Familiar with mainstream architectures (CNNs, Transformers, Diffusion models, etc.);
  • Knowledge of model deployment and inference optimization (ONNX / TensorRT / distributed training);
  • Strong engineering mindset, clean coding habits, and ability to work independently.

Preferred Qualifications:

  • Experience with large-scale model training or multi-modal (vision-language) learning;
  • Familiar with distributed or mixed-precision training, LoRA/SFT fine-tuning, or model compression/distillation;
  • Knowledge of cloud-based training and deployment (Docker, Kubernetes, AWS, GCP);
  • Prior experience contributing to open-source projects, AI competitions (e.g., Kaggle), or academic publications.

Benefits:

  • Gain hands-on experience in a leading AI company at the forefront of technological advancements.
  • Work closely with a diverse team of experts and professionals in the AI industry.
  • Opportunity to showcase your skills and potentially secure a future career with the company.
  • Official annual leaves and medical leaves given.
  • Potential for performance-based incentives and awards, or opportunity to be converted into full time staff.

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