Deep Learning Engineer

Snap Inc. is a camera company. We believe that reinventing the camera represents our greatest opportunity to improve the way people live and communicate. Our products empower people to express themselves, live in the moment, learn about the world, and have fun together. 

Snapchat is the camera used by millions of people every day to Snap with family, watch Stories from friends, see events from around the world, and explore expertly-curated content from top publishers. In short, we are a passionate team working hard to build the best platform in the world for communication and storytelling.

We’re looking for an exceptional Deep Learning (DL) Engineer to help us improve our conversational technologies. This includes building deep learning speech and NLP models that will be used by millions of users throughout the world. Applicants need to demonstrate production proven experience together with exceptional skills in research and implementation of algorithms in DL, ML, NLP and signal processing.

Responsibilities

  • End-to-end responsibility of deep learning and machine learning models, from research, design and up to implementation.
  • Train, benchmark, deploy and monitor machine learning models throughout the production pipeline

Minimum Qualifications:

  • Master’s or PHD in Computer Science or another quantitative field
  • 5+ years of experience in research teams
  • 5+ years of experience using Python/Go/Java
  • Proven experience in manipulating data sets and building statistical models
  • Proven experience building ML/DL solutions in production (using TensorFlow/Pytorch)
  • Proven experience working within a cloud based environment

Preferred Qualifications:

  • Deep and broad understanding of foundation up to state-of-the-art machine learning deep learning, deep learning and advanced statistical techniques
  • Excellent written and verbal communication skills
  • A drive to learn new technologies and techniques
  • Advantage: proven production based experience in developing systems with deep learning networks for voice and/or NLP
  • Advantage: working in research for high scale consumer systems
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