Machine Learning Engineer Intern

Description du poste:

Description

The Impact You’ll Be Contributing to Moloco:

We are an engineering company founded by engineers. We understand the value of a strong engineering team and strive to hire only the best engineering interns.

We are seeking exceptional Machine Learning interns to join us in building a state-of-the-art machine learning system. Moloco’s programmatic advertising engine is powered by custom deep neural network models that handle 1M+ QPS at 7 ms prediction latencies. As an intern, you can expect to be a full member of the team you join and will be treated as a junior engineer, with the same expectations, project opportunities and responsibilities. Some examples of past intern projects are:

  • Conducting experiments on state-of-the-art machine learning models using Tensorflow for real world, large scale problems.
  • Constructing and enhancing data pipelines for model training and serving using Google cloud products such as Apache Beam/Dataflow, BigQuery, and BigTable.
  • Building machine learning productivity tools (e.g. model quality measurement), deploy them in Kubernetes, and help model engineers adopt them.

Minimum Qualifications:

  • Able and willing to work from our Seattle, WA or Redwood City, CA office.
  • Currently enrolled in, or recently graduated from (within the last 12-months), a Bachelor's, Master’s or PhD program in Computer Science, or a related technical field.
  • Candidates pursuing a Bachelor's or Master's degree must be graduating and obtaining degree by June of 2025.

Preferred Qualifications:

  • Strong background in data structures and algorithms.
  • Strong coding and problem solving skills.
  • Familiar with distributed systems and/or databases.
  • Fluent with at least one programming language.

Internships are full-time (40-hours per week) and 12-weeks in duration during the summer, between May and September 2024. Interns are expected to work in office each working day for the first two weeks, and three days per week for the remainder of the internship.



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