Cynapse Pte Ltd is hiring for a Machine Learning Engineer Intern (Computer Vision & AI) - August 2026 internship — a 6-month, on-site Software Engineering role based in 71 Ayer Rajah Crescent #04-20/21, Singapore, 139951, Singapore. It offers an allowance of SGD 1,100-1,500/mo. It is open to university students, typically in Year 2–4. Applicants with experience in Deep learning model training, Linux, PyTorch, TensorFlow, and Python are a strong fit.
At SGD 1,100/month, this pays below the typical SGD 3,900/month for Software Engineering internships in Singapore.
About this role
[The Role] We are seeking a hands-on Machine Learning Engineer Intern to join our Model Engineering Team with a focus on Computer Vision and modern AI. This role is designed for builders who are passionate about training deep learning models, refining architectures, and scaling real-world vision systems. You will work closely with experienced engineers on production-grade models, ranging from standard object detectors to cutting-edge zero-shot and open-vocabulary architectures. This is an ideal role for those who enjoy running experiments, analysing model behaviour, and driving measurable performance improvements.
Responsibilities
[What You’ll Do] Model Training & Fine-Tuning: Train, evaluate, and improve deep learning models across a variety of tasks, including classification, object detection, segmentation, and action recognition. Architecture & AI Exploration: Research and experiment with CNNs, Transformers, and Foundation Models. You will explore the integration of modern AI to enhance open-vocabulary detection and zero-shot capabilities. Failure Analysis & Data Refinement: Debug model failures (false positives/negatives) and implement solutions through targeted data annotation, cleaning, or improved inference strategies to ensure model robustness. Data & ML Engineering: Manage large-scale datasets, including preprocessing and versioning, to ensure high-fidelity and reproducible experiments. Pipeline Automation: Contribute to the development and optimization of automated training and evaluation pipelines to improve reliability and deployment efficiency. [Who This Role Is For] Builders: You prefer hands-on engineering and practical implementation over purely theoretical research. Experimenters: You enjoy the iterative process of testing different architectures, hyperparameters, and datasets to maximize performance. Problem Solvers: You are curious about root causes and enjoy the "detective work" required for model debugging and data-driven improvements. Pragmatists: You are excited to see your models and automated systems successfully deployed in real-world production environments.
Requirements
[Requirements] Pursuing or completed a degree in Computer Science, AI, Machine Learning, or a related technical field. Strong interest in deep learning model training, experimentation, and data-centric AI. Proficiency in Python and experience with PyTorch or TensorFlow. Competency in a Linux environment (SSH, shell scripting, and CLI-based file management). [Bonus Points] Hands-on Experience: Previous work with specialized CV frameworks or comparing multiple architectures. Modern AI Knowledge: Familiarity with vision-language models or zero-shot detection. MLOps Tools: Experience with Git, Docker, or experiment tracking tools (e.g., Weights & Biases, MLflow). Video Processing: Knowledge of OpenCV, FFmpeg, or handling video streams. [Internship Details] Duration: Minimum 6 months (flexible). Commitment: 4–5 days per week. Location: Singapore-based. Please note that due to the nature of the role, the position is considered only for candidates who are based in Singapore or have experience studying and/or working in Singapore.
Benefits
Unique opportunity to work with a talented global team on cutting edge technologies Exciting work environment with flexible hours
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