Software Engineer, Machine Learning

Lyft, San Francisco, CA

Lyft is your friend with a car, whenever you need one

We are looking for highly motivated Machine Learning Engineers that will impact all aspects of Lyft’s business by enabling tools and scalable platforms for making model training, deployment and testing easier. As part of the role, you will work closely with our Product, Data Science and Engineering teams to solve some exciting bleeding edge Machine Learning problems that enable all aspects of the core product including marketplace design, fraud, growth, mapping and self-driving cars.

The ideal candidate is a critical thinker, understands machine learning workflows, is passionate about solving business problems using data, and is excited about working in a fast-paced, innovative and collegial environment.


  • Work with Product Manager and Data Scientists to frame a problem within the business context.
  • Design the architecture and tooling to train and launch the ML models.
  • Build the micro-services and platforms to enable the use of the ML models.Collaborate with Data scientists on the modeling code and then prepare the algorithms for experimentation in simulations and production.
  • Analyze experimental and observational data; communicate findings; facilitate launch decisions.
  • Write well-crafted, well-tested, readable, maintainable production-ready code. Quickly.
  • Participate in code reviews to ensure code quality and distribute knowledge.


  • B.S., M.S. or Ph.D. in Computer Science.
  • 4+ years (or Ph.D. with 2+ years) of professional or research experience with models, code or platforms using Machine learning.
  • Ability and interest in understanding machine learning models.
  • Knowledge of ML libraries like scikit-learn, Tensorflow, Caffe, Keras, etc.
  • Experience with object-oriented programming Proficiency in building microservices and APIs.
  • Great oral and written communication skills.

Experience working with AWS or Google Cloud is a plus.
Experience or understanding of distributed data compute stacks - Spark, MapReduce, Hadoop, etc.

About Lyft

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Want to learn more about Lyft? Visit Lyft's website.