Deep Learning CV Intern: Production-Ready Models

Danone Specialized Nutrition (Singapore) Private Limited; Singapore; Hybrid; SGD 11,000 - 28,000; Full time

Job summary

Danone Digital Lab Singapore is seeking a Deep Learning intern to help improve production-facing computer vision models. You will design, train, and evaluate CV models (classification, detection, segmentation) and run experiments on architectures, data pipelines, and training strategies.

Ideal candidates have strong Python skills, hands-on DL with TensorFlow or PyTorch, and a portfolio showcasing DL work. The role emphasizes collaboration with stakeholders and opportunities for hands-on learning

Qualifications

• Proven Python programming skills for ML workflows.
• Hands-on experience with training/evaluating DL models using TensorFlow or PyTorch.
• Experience with CV tasks such as image classification, object detection, or segmentation.
• Ability to conduct experiments including architecture choices, hyperparameter tuning, and error analysis.
• Portfolio/GitHub/publication showcasing deep learning work.

Responsibilities

• Design and implement improvements to computer vision models (classification, detection, segmentation).
• Run experiments on model architectures, training strategies, and data pipelines.
• Review and implement ideas from recent DL/CV literature.
• Define evaluation metrics and benchmark model performance.
• Work with real-world image datasets (noisy, imbalanced, imperfect).
• Work independently with minimal supervision and strong task management/communication.
• Present results and trade-offs to technical and non-technical stakeholders.

Skills

Python programming

Computer vision fundamentals

Experiment design

Communication

Tools

TensorFlow

PyTorch

MLflow

Docker

Job description

Danone Digital Lab Singapore is seeking a Deep Learning intern to help improve production-facing computer vision models. You will design, train, and evaluate CV models (classification, detection, segmentation) and run experiments on architectures, data pipelines, and training strategies.

Ideal candidates have strong Python skills, hands-on DL with TensorFlow or PyTorch, and a portfolio showcasing DL work. The role emphasizes collaboration with stakeholders and opportunities for hands-on learning