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Machine Learning Engineer

2 months ago

New York, New York, United States pluscompany Full time

Job Title: Associate Machine Learning Engineer

Salary: $110,000 - $130,000 USD

Summary:

The Associate Machine Learning Engineer is responsible for designing, developing, and maintaining machine learning processes to improve the performance of PlusCompany's marketing technology platform. The ideal candidate will have a strong foundation in statistics, machine learning, and computer science, mathematical optimization, programming languages such as Python, and familiarity with cloud platforms such as AWS.

Key Responsibilities:

  • Develop and maintain machine learning systems to improve the accuracy and efficiency of PlusCompany's marketing analytics platform.
  • Design and develop processes to clean, prepare, and analyze large amounts of data to train and evaluate predictive models.
  • Collaborate with engineers and product managers to identify and prioritize development work in an Agile software development environment.
  • Provide support to users and stakeholders of the product for successful execution of machine learning tasks and evaluation of their results.
  • Stay up-to-date on the latest advancements in machine learning and artificial intelligence.

Requirements:

  • Masters degree in Computer Science, Statistics, Mathematics, or a related quantitative field such as Engineering, Economics, Physics, Biology, or Psychology.
  • Strong programming skills in Python.
  • Experience with machine learning libraries such as scikit-learn and TensorFlow.
  • Familiarity with handling large amounts of data using SQL and Spark.
  • Strong analytical and problem-solving skills.
  • Excellent communication and teamwork skills.
  • Business domain appreciation and fascination.

Preferred Qualifications:

  • Experience with cloud computing platforms such as AWS.
  • Experience with other programming languages such as R and C++.
  • Distributed Computing experience.
  • Familiarity with Agile practices.
  • Training in Economics and Econometrics.
  • Exposure to the Digital Marketing and Advertising Ecosystem.