Machine Learning Engineer – Digital Nova Scotia – Leading Digital Industry

Machine Learning Engineer


As a Machine Learning Engineer, you will be part of a Canada-based team working remotely with a leading US scale-up.  Your team will operate alongside many other talented developers and data scientists in Canada, and you will be an integral part of the tech community that MobSquad has built.

This role requires someone who has demonstrated an ability to use data to train models which can be used to automate processes such as image classification, speech recognition, and forecasting.  The ideal candidate has deployed or attempted to execute Artificial Intelligence theories from various Machine Learning (ML) models and algorithms, and they also have familiarity with data science engineering.  The candidate should be able to apply their analytical skills to develop large-scale ML models that reveal the value in data.  They are able to understand business objectives from a broader team and build customized models and processes to enable delivery of the business objectives.


  • You have an advanced degree (M.S. or PhD) in Computer Science, Engineering, Mathematics, Physics, or a comparable analytical field from an accredited institution
  • You have over five years of experience working with deep learning frameworks (TensorFlow, Keras)
  • You have over five years of experience with relevant languages (Python, Java) and libraries (scikit-learn, Pandas)
  • You have over five years of experience developing unique algorithms
  • You have strong experience creating and deploying machine learning models
  • You have demonstrated knowledge of relevant libraries and operating systems (OpenCV, Linux)
  • You have knowledge of SQL (MySQL, PostgreSQL) and NoSQL (MongoDB, Cassandra, HBase) databases
  • You have strong attention to detail, translating to strength in data quality verification to enable clean data at all times
  • You have work/project history reflective of a self-motivated professional who excels when given open-ended problems and broadly-defined goals, having an innate desire to build models and algorithms that reveal the patterns and relationships in data that can be leveraged to provide business value