Machine Learning Engineer (Computer vision)

Key Skills

AWS, Azure, Computer Vision (CV), Deep Learning, Git, Linux Operating system, Machine learning techniques, Python Programming, PyTorch, TensorFlow

Job Description

Constructor is an all-in-one platform for education and research. With expertise in machine intelligence and data science, Constructor is built to cater to the needs of schools, higher education, corporate training, alternative credentials, and professional sports, offering solutions for teaching and administration, learning and research.

From infrastructure to applications, Constructor elevates learning experiences, empowers educators, and drives research breakthroughs.

Our headquarter is situated in Switzerland. Also we have entities in Germany, Bulgaria, Serbia, Turkey, and Singapore.

DUTIES & RESPONSIBILITIES:

• Participating in research and development process of computer vision models (detection, segmentation, recognition, generative models)
• Deploying of computer vision machine learning models in products
• Optimizing computer vision machine learning models
• Multimodality approaches (text, images)
• Increasing accuracy and performance of computer vision machine learning algorithms
• Developing pipelines for data collection and preparation
• Algorithms quality validation and monitoring
• Developing services for machine learning models launch
• Bug fixing support

QUALIFICATION & EXPERIENCE:

• Master’s degree in Computer Science, Mathematics, Physics or similar field.
• 3+ years of machine learning models developing experience.
• Solid knowledge of Python.
• Experience with modern deep learning frameworks like PyTorch, Tensorflow.
• Knowledge of main methods of supervised learning (regression, classification), unsupervised learning (cluster analysis, dimensionality reduction), machine learning models validation, deep learning models optimization.
• Experience in algorithms developing for image classification, object detection, object tracking, segmentation.
• Experience in computer vision generative approaches (GAN, VAE, Diffusion models).
• Experience with MLOps tools (CVAT, Label studio, DVC, MLflow, Weights & Biases).
• Experience in developing cloud service Azure/AWS.
• Experience with Git, Linux.