Machine Learning Engineer

Tasks

• Focus on the core aspects of machine learning, building and reimplementing models, evaluating models, and supporting real-world product features
• Design and implementation of data systems to support the development of personalized solutions and applications
• Use of web processing technologies, engineering, model selection, and automated implementation
• Understanding related APIs and algorithms, as well as working with machine learning algorithms (in addition to statistical analysis)

Requirements

• A friendly, people-centered approach to machine learning for tackling complex economic challenges
• Knowledge of statistical and mathematical concepts relevant to machine learning, such as principles of (expert) models and optimization (e.g., convolutional/recurrent networks)
• Knowledge of classification and model evaluation tools (including feature selection, unsupervised and supervised learning, and optimization)
• Knowledge of ensemble learning methods and hyperparameter tuning
• Familiarity with computer vision and natural language processing to enable the identification and resolution of visual tasks and to increase efficiency
• Research experience in machine learning, data science, or related fields