AI Engineer (Computer Vision, Model Engineering)

at  CYNAPSE PTE LTD

ABOUT CYNAPSE

Cynapse is an awarded AI Software Product company specializing in Enterprise-grade Vision AI in highly challenging environments. cynapse’s software platform is leveraging cutting-edge cloud/on-premise/edge platforms, advanced computer vision algorithms, advanced ML concepts & models, and more.
The company’s Headquarter is located in Singapore (one-north Area)

JOB DESCRIPTION

Cynapse is looking for a talented and highly motivated Computer Vision & Machine Learning Developer to join our AI team that delivers a challenging, enterprise-scale Video Content Analytics solutions to global customers. You will conform to high standards of design and coding, working in a cutting-edge, dynamic and professionally challenging environment.

QUALIFICATIONS

• Bachelor’s degree in Computer Science, Data Science, Artificial intelligence, mathematics, Electrical Engineering, or a related field.
• Solid understanding of machine learning concepts, particularly neural networks and their applications in computer vision (e.g., convolutional neural networks, transfer learning, and deep learning architectures).
• Proficient in one or more popular machine learning frameworks such as TensorFlow, PyTorch, or similar.
• Experienced with computer vision libraries like OpenCV, scikit-image, or equivalent.
• Strong programming skills in Python, with expertise in using tools like NumPy, Pandas, and Matplotlib for data manipulation and visualization.
• Knowledge of data preprocessing techniques, including image augmentation, normalization, and resizing.
• Basic understanding of MLOps practices, including version control, continuous integration, and continuous deployment (CI/CD).
• Strong analytical and problem-solving skills with attention to detail.
• Good communication skills, both written and verbal, with the ability to work collaboratively in a team environment.
• Eagerness to learn and adapt to new tools and technologies in the rapidly evolving fields of machine learning, computer vision, and MLOps.
• (Optional) Experience with cloud platforms like AWS, GCP, or Azure is a plus.
• (Optional) Knowledge of Docker or other containerization tools for model deployment.
• (Optional) Familiarity with MLOps tools like MLflow, Kubeflow, or similar is a plus.

• Assist in the development and training of computer vision models using state-of-the-art machine learning techniques.
• Work with large datasets for model training.
• Collaborate with engineers to implement and fine-tune models, focusing on performance, accuracy, and scalability.
• Contribute to the deployment and monitoring of trained models in production environments, ensuring robustness and reliability.
• Participate in the development and maintenance of MLOps pipelines, automating the process of model training, deployment, and monitoring.
• Conduct research to explore and implement the latest computer vision and MLOps techniques and technologies.
• Maintain and update model pipelines, ensuring they meet project requirements and deadlines.