ML Software Engineer, ETA

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

We are hiring a Machine Learning Engineer to join our ETA team. Our team builds and maintains Lyft's system responsible for estimating/predicting ETAs for every ride request on our platform. ETAs play a critical role in matching decisions, pricing estimates and overall user experience. Low latency, high reliability and high accuracy are paramount for our success. 

If you are a critical thinker with experience in machine learning workflows and writing reliable code, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you. 

Our technology stack runs on AWS, Kubernetes, Go, Spark, Python and Apache Airflow. In this role, you will work with incredibly passionate and talented colleagues from software engineering, machine learning and data science on building rideshare experiences that delight millions of riders and drivers. 

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

• B.S., M.S., or Ph.D. in Computer Science or other quantitative fields or related work experience
• 3+ years of Machine Learning experience

• Nice-to-have: Experience with big data processing / distributed data pipelines and tools such as Apache Airflow and Spark

• Ability to work in distributed teams spread across time zones. (North America and Europe)