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Machine Learning Infrastructure Engineer

Company Name: Spotify
Location: New York
Date Posted: 21st May, 2018
Description:

What you’ll do

  • Build infrastructure to apply machine learning methods to massive data sets in production environments
  • Collaborate with cross functional agile teams of software engineers, data engineers, ML experts, and others in building new product features
  • Contribute to new and existing Spotify open source machine learning and data processing products (scio, featran, zoltar)
  • Leverage your experience to drive best practices in ML and data engineering
  • Gain a deep understanding of various models (collaborative filtering, NLP, deep learning) in order to understand their tradeoffs and bottlenecks
  • Design machine learning platforms and pipelines for training and running machine learning models on distributed systems
  • Determine the feasibility of projects through quick prototyping with respect to performance, quality, time and cost using Agile methodologies
Qualification:

Skills Required -

  • You have development experience with an object-oriented programming language such as C++ or Java and/or functional programming languages
  • You have previous industry experience with ML systems using frameworks such as Scikit-learn and Tensorflow
  • You have previously built APIs and libraries for Java, Scala or Python
  • You care about agile software processes, data-driven development, reliability, and responsible experimentation
  • You preferably have experience with data processing and storage frameworks like Google Cloud Dataflow, Hadoop, Scalding, Spark, Storm, Cassandra, Kafka, etc.
  • You preferably have machine learning publications or open source contributions to share with us
  • Skilled communicator and have a proven record of leading work across disciplines