AI Deep Learning Pipeline Specialist

3 days ago


Singapore beBeeArtificial Full time $6,000 - $8,000
Deep Learning Engineer Opportunity

Cynapse is a pioneering AI software company that specializes in developing cutting-edge Video Intelligence Solutions. Our innovative technology, powered by Generative AI, empowers organizations to enhance safety, operational efficiency, and security in complex environments.

Led by a global team with a proven track record of scaling startups into market leaders, we foster innovation, collaboration, and diverse perspectives. As a leading provider of video intelligence solutions worldwide, Cynapse serves clients globally and redefines what's possible with video analytics.

Job Overview
  • This role offers an exciting opportunity to gain hands-on experience across the entire deep learning pipeline, including data preparation, model training, evaluation, and deployment.
Key Responsibilities
  • Work closely with engineers to design, build, and refine deep learning models for various Computer Vision tasks.
  • Contribute to the optimization of models and pipelines by conducting experiments, analyzing results, and helping to improve model performance.
  • Gain exposure to modern tools like Docker, CI/CD, and cloud platforms to support scalable, reliable model deployment.
Requirements
  • Currently pursuing or completed a Diploma/ Bachelor/ Master's in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related field.
  • Basic understanding of machine learning concepts, demonstrated through the completion of at least one hands-on university or online module.
  • Proficiency in Python programming (minimum 6 months of hands-on experience or equivalent AI/ML project experience, including GitHub contributions).
  • Familiarity with at least one deep learning framework such as TensorFlow, PyTorch, or similar.
Preferred Skills
  • Familiarity with building and optimizing ML pipelines, including data preprocessing, model training, testing, and deployment.
  • Experience in software engineering practices like version control (Git), CI/CD pipelines, or Docker for containerization.
  • Exposure to cloud platforms (AWS, GCP, Azure) for deploying and managing ML models in production.
  • Knowledge of computer vision concepts and libraries (e.g., OpenCV).

Duration: Minimum 4 months internship duration, negotiable based on the candidate's schedule.


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