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Professional development

Bandung

Quantus Telematika Indonesia Is an IT software startup, with innovation as the company driver, the main ingredient of QTI IT system solution. We take our organization as a slim, engineering-oriented structure. Eliminate as much as communication barrier to provide effective control and collaboration.

Some of our engineers have been in the industry for over 15 years; QTI engineers experienced the bolts and nuts of complicated IT systems, over-hyped IT jargons, unrealistic targets and ups and downs of IT business. These experiences made us values street-smart engineering, and avoid shortcuts.

Information Technology and Services

Pt. Quantus Telematika Indonesia

Indonesia

PT. Quantus Telematika Indonesia

Degree in Computer Science, Information System, Software Engineering, Mathematics, or Related Field

Programming Skills : Python including object-oriented programming, syntax, functions, flow control statements, libraries, and documentation.

Data visualization, The ability to present data analysis and processing results to non-technical members of the organization.

Analytical and problem-solving skills. The ability to analyze data, identify trends, and develop solutions. 

Requirements for Computer Vision Engineer

Familiarity and Experience with computer vision libraries, like OpenCV or Dlib, for developing and implementing vision-based models

Knowledge of machine learning and deep learning frameworks, including TensorFlow or PyTorch

Knowledge of neural networks – especially convolutional neural networks (CNNs)

Understanding of image processing techniques – including filtering, edge detection, and image segmentation– for manipulating images

Mathematical skills in linear algebra, calculus, probability, geometry, and statistics for algorithm development and data analysis 

Able to develop near real time and real time image and object detection for analysis.

Image analysis, The ability to develop image analysis algorithms and design platforms for image processing and visualization.

Design, implement, and optimize NLP models for various applications, including but not limited to text classification, sentiment analysis, entity recognition, and language generation.

Develop effective strategies for cleaning, preprocessing, and augmenting text data to enhance model performance.

Stay abreast of the latest advancements in NLP and contribute to the development of custom algorithms tailored to specific project requirements.

Train and fine-tune NLP models using appropriate frameworks (e.g., TensorFlow, PyTorch) and evaluate their performance using relevant metrics.

Work closely with cross-functional teams to integrate NLP solutions into existing systems and applications.

Stay informed about the latest research in NLP, contribute to internal knowledge sharing, and explore innovative approaches to solve language-related challenges.

Maintain thorough documentation for models, algorithms, and processes, ensuring that knowledge is shared and accessible within the team.

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