Machine Learning Engineer

Redfin Redfin · Seattle · Detroit, MI

Machine Learning Engineer responsible for designing and developing platforms and frameworks for automated data-driven decision-making, including gathering data, determining statistical algorithms and models, building services for model interaction and hosting, and developing tools for monitoring performance. The role involves collaboration with data scientists and integration into business processes.

What you'd actually do

  1. Collaborate with data scientists to develop algorithms and tools for training and running simulations
  2. Build services to interact with machine learning models through simulations
  3. Participate in code reviews to ensure code quality and share best practices
  4. Develop services that host the trained models and work with other application teams to integrate them into business processes
  5. Gather and analyze large datasets and develop data model pipelines

Skills

Required

  • Master’s degree in software development, computer science, algorithm design, artificial intelligence, or machine learning or equivalent experience
  • programming experience, including Java, or Python

Nice to have

  • 1 year of experience in machine learning and using libraries such as Scikit-learn, TensorFlow, Caffe, Keras, etc.
  • 1 year of experience working with large datasets, structured and unstructured
  • 1 year of experience with the Hadoop ecosystem (Apache Hive, Pig, HBase and Kafka)
  • 1 year of experience with distributed computing platforms, such as Spark, and user interface frameworks, such as Angular or React
  • 1 year of experience with cloud computing providers such as AWS or Azure
  • Ph.D. in software development, computer science, algorithm design, artificial intelligence, or machine learning or equivalent experience
  • Proficiency in the Microsoft Office suite
  • Strong object-oriented programming skills, including proficiency in Java, Scala, C/C++ or Python
  • Knowledge of big data

What the JD emphasized

  • equivalent experience

Other signals

  • design and develop platforms and frameworks for automated decision-making
  • develop algorithms and tools for training and running simulations
  • build services to interact with machine learning models
  • develop services that host trained models
  • gather and analyze large datasets and develop data model pipelines
  • develop algorithms that drive automated data-driven decision-making
  • build tools for monitoring the performance of machine learning applications