INTERN - Data Engineering

| Bellevue
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Candidate profile: Required – Statistics focused academic background. Desirable – Sequence modelling experience (Markov Chains, RNNs, LSTM, Sequence-to-sequence, Transformer networks), and Reinforcement Learning.

Project: There are four candidate projects for a ten-week internship in the Process Understanding pillar. The intern’s prior experiences will determine which one will be most appropriate. For illustration only one is described below:

Determine how Transformer Networks can be applied to the LPM discovery problem and measure how they perform compared to the auto regressive HMM approach

Week:

  1. Introduction and literature review.
  2. Literature review.
  3. Analyze data and see how UiPath has adapted AR HMMs to the problem.
  4. Adapt Transformer Network Implementations to fit the input data.
  5. Model optimization.
  6. Analyze and summarize results.
  7. Peer review.
  8. Make changes to the implementation and continue to experiment.
  9. Final presentation of results to all stakeholders.
  10. Handover, feedback sessions and social.

 

 

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Location

10400 NE 4th St., Bellevue, WA 98004

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