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Machine Learning Engineer, Voci (Remote, US)

None
Medallia
ago
remote fulltime Speaker

As a Machine Learning Engineer in the speech research group at Medallia, you will help to shape the future of our multilingual speech products and services. You will be responsible for conducting research and development activities leading to faster and more accurate language and accent verification systems, language and accent classification systems, and language and accent clustering systems. You will be working in all aspects from validating the published state-of-the-art, prototyping novel algorithms, training and testing machine learning models, integrating components into end-to-end systems, writing and testing production code, and tracing error reports from the field. The linguistic classification libraries that you help to build will be deployed primarily within our high-speech, state-of-the-art multilingual speech transcription server.

What do we look for? Engineers who thrive at Medallia have a few key traits:

Able to take ownership of a problem, propose solutions and drive them to successful completion;

Driven to be the best version of themselves on a daily basis; Care about their work, their team and their company; Expect their ideas to be challenged because they believe that the best ideas can come from anywhere; View feedback as a gift that they give and receive

Qualifications:

  • MS in Computer Science, Electrical Engineering, or Computational Statistics
  • 1+ years’ experience executing machine learning experiments
  • 2+ years’ experience programming in C, C++, and/or Python
  • Experience with algorithm design and/or analysis in MATLAB, Mathematica, R, or NumPy
  • Familiarity with big data, and comfort with organizing, validating and modifying large real-world data sets
  • Good technical communication skills in English

Bonus Points:

  • Experience in speech processing and managing extensive audio data sets
  • Prior system development experience in language recognition, speaker recognition, or other audio classification technologies
  • Experience in scientific and numerical programming in C++
  • Experience in object-oriented design, analysis, and programming
  • Comfort in the *nix environment, and experience with bash and/or Perl
  • Experience using version control systems (e.g., git)
  • Spoken fluency in at least one additional language (besides English)

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