Machine Learning Engineer

In this role, youll be responsible for building machine learning-based systems and conducting data analysis that improves the quality of our large geospatial data. You’ll be developing models to extract information, using outlier detection to identify anomalies, and applying data science methods to quantify the quality of our data. You will take part in the development, integration, productionization, and deployment of the models at scale, which would require a good combination of data science and software development.

Responsibilities:

• Development of machine learning models
• Building and maintaining software development solutions
• Provide insights by applying data science methods
• Take ownership of delivering features and improvements on time
  
  

Requirements

Must-have Qualifications:

• Able to wear multiple hats, do what it takes ability and attitude
• Strong programming skills and extensive experience with Python, Scala and/or Java
• Professional experience working with machine learning and data science, such as classification, feature engineering, clustering, anomaly detection and neural networks
• Knowledgeable in classic machine learning algorithms (SVM, Random Forest, Naive Bayes, KNN etc).
• Experience with frameworks such as Sklearn, Numpy, Pandas
• Excellent analytical and problem-solving skills
• Excellent oral and written communication skills
  
  

Extra Merit Qualifications:

• Experience using deep learning libraries and platforms, such as PyTorch, TensorFlow, Keras
• Knowledge in at least one of the following: NLP, information retrieval, data mining
• Ability to do statistical modelling and building predictive models