Machine Learning Engineer


  • Design and develop scalable ML/AI solutions to solve diverse business challenges by deriving features from rich data sources, training, evaluating and deploying models to production using cutting edge technologies

  • Gather and analyze data to perform statistical analysis, identify key factors and build comprehensive visualizations to report findings

  • Utilize statistical methods to process, clean and validate data for uniformity and accuracy

  • Create and maintain end-to-end data pipelines and APIs according to business requirements

  • Communicate analytic solutions to stakeholders and implement improvements as needed to operational systems


  • Experience using statistical computer languages, such as R or Python (preferred)

  • Experience working with large data sets (> 1TB) and using big data solutions such as Hadoop, Hive, Spark, Storm, MongoDB etc.

  • Experience specifically with deep learning (e.g., CNN, RNN, LSTM) and NLP frameworks

  • Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, etc. and their real-world advantages/drawbacks

  • Rigorous understanding of statistics and ability to discern appropriate statistical techniques to problem-solve

  • Proficiency with writing SQL queries

  • Experience with data visualization tools, such as Tableau, is a plus

  • Prior work experience in the financial industry is a plus

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