Cynapse Pte Ltd Hiring! Machine Learning Engineer Intern (Computer Vision - AI) in , Earn up to SGD 1,500 - Ricebowl

Company

Cynapse Pte Ltd

Designation

Machine Learning Engineer Intern (Computer Vision & AI)

Date Listed

06 May 2026

Job Type

Entry Level / Junior Executive

Job Period

From Aug 2026, For At Least 6 Months

Profession

IT / Information Technology

Industry

Artificial Intelligence / Smart Automation

Location Name

71 Ayer Rajah Crescent, #04 21, SingaporeSingapore 139951, Singapore

Address

71 Ayer Rajah Cres., #04 21, Singapore 139951

Map

Allowance / Remuneration

$1,100 - 1,500 monthly

Company Profile

About Cynapse

Cynapse is a leading AI software company specializing in enterprise-grade Video Intelligence Solutions Powered by Generative AI, tailored to meet the unique challenges of various industries. Our vertical-specific solutions empower organizations to enhance safety, operational efficiency, and security in complex environments such as roads, seaports, airports, and cities. By combining advanced Vision AI with Generative AI, we continually push the boundaries of video analytics, delivering insights and automation that transform operations.Led by a global team with a proven track record of scaling startups into market leaders, we foster innovation, collaboration, and diverse perspectives. Headquartered from US, Cynapse serves clients worldwide, redefining what's possible with video intelligence.

Job Description

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.

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

• 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.

Application Instructions

Please apply for this position by submitting your text CV with your response to the following questions:

1. Is this internship credit-bearing (graded)?
2. Are you legally authorized to work in Singapore?
3. Will you require sponsorship now or in future to work in Singapore?
4. Are you able to commit to this internship for at least 4 days a week for 6 months?

Kindly note that only shortlisted candidates will be notified.