Engineering Team | Santa Barbara or New York City

cielo24’s mission is to develop the next generation media experience (contextual video with media insights) to help clients maximize the value of their media content. cielo24’s media analysis platform utilizes automation and massive crowd sourcing to create high-quality media data including captions, timed transcripts, indexes and media intelligence. To support us in this mission we are searching for an individual who sits at the intersection of data science and engineering and is excited about directly participating in the full-stack development of our next generation media insight engine.

Working directly with the CTO and a small internal team, the Data Engineer is responsible for providing expertise and guidance on machine learning related topics and contributing directly to their implementation. In addition to a deep engineering background, the ideal candidate will have strong communications and product development skills, and would be comfortable working directly with prospective partners and clients to capture requirements and foster relationships.

Responsibilities

  • Be the authoritative voice of Data Science at cielo24.
  • Lead the implementation of machine learning systems, infrastructure, and products
  • Contribute to the development of our next generation in-house infrastructure platform
  • Guide other engineers to a better understanding of machine learning and large-scale data processing

Requirements

Technical:

  • Significant backend engineering experience, ideally having led the implementation of a complete system which is in moderate or large-scale production use.
  • Notable professional experience in either machine learning or data science.
  • Bachelor’s or Graduate Degree in quantitative discipline (Statistics, Math, Computer Science).
  • Professional experience with machine learning, data mining, and/or statistical analysis.
  • Proficiency with Python.
  • Experience with containerized deployment or infrastructure orchestration at scale.

Non-Technical:

  • Excellent analytical and problem-solving skills.
  • Strong oral and written communication skills.
  • A passion for empirical research and for answering hard questions with data.
  • Proven record of solving challenging problems in academia and/or industry.
  • Eagerness to collaborate with both technical and non-technical colleagues, product management, marketing, and executive leadership.

 

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