ML Software Engineer, Eta

Lyft Lyft · Consumer · San Francisco, CA · Mapping

ML Engineer role focused on building and maintaining Lyft's ETA prediction system, which requires low latency, high reliability, and high accuracy for millions of daily requests. The role involves developing ML models, writing production-quality code, and working with a stack including AWS, Kubernetes, Spark, and Airflow.

What you'd actually do

  1. Perform data analysis and build proof-of-concept to explore and compare ML and non-ML solutions
  2. Be able to make effective tradeoffs between model accuracy, its productization complexity and runtime performance
  3. Develop statistical, machine learning, or optimization models
  4. Write production quality code that can scale well to serve millions of requests per day
  5. Participate in code reviews, design reviews, production on-call support and incident triaging process.

Skills

Required

  • Machine Learning experience
  • production quality code
  • scale well
  • data analysis
  • statistical models
  • machine learning models
  • optimization models
  • code reviews
  • design reviews
  • production on-call support
  • incident triaging

Nice to have

  • big data processing
  • distributed data pipelines
  • Apache Airflow
  • Spark

What the JD emphasized

  • low latency
  • high reliability
  • high accuracy
  • production quality code
  • scale well to serve millions of requests per day

Other signals

  • ETA prediction
  • low latency
  • high reliability
  • high accuracy
  • millions of requests per day