Associate Machine Learning Engineer

at  Lyft

At Lyft, our mission is to improve people’s lives with the world’s best transportation. To do this, we start with our own community by creating an open, inclusive, and diverse organization.
With over half a billion rides and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Marketplace, Mapping, Fraud, Growth and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building next-generation platform for low-cost, ultra-immersive transportation to improve people’s lives warrants modern ML utilizing peta-byte scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business.
If you are a critical thinker with experience in machine learning workflows, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you.
As an associate machine learning engineer, you will be developing and launching the algorithms that power the platform’s core services. Compared to similarly-sized technology companies, the set of problems that we tackle is incredibly diverse. They cut across transportation, economics, forecasting, mapping, personalization, and adaptive control. We are hiring motivated experts in each of these fields. We’re looking for someone who is passionate about solving problems with data, building reliable ML systems, and is excited about working in a fast-paced, innovative, and collegial environment.
You will report to a Software Engineering Machine Learning Manager.

QUALIFICATIONS:

• B.S., M.S., or Ph.D. in Computer Science or other quantitative fields or related work experience
• Passion for building impactful machine learning models leveraging expertise in one or multiple fields.
• Proficiency in Python, Golang, or other programming language
• Excellent communication skills and fluency in English
• Strong understanding of Machine Learning methodologies, including supervised learning, forecasting, recommendation systems, reinforcement learning, and multi-armed bandits

• Partner with Engineers, Data Scientists, Product Managers, and Business Partners to apply machine learning for business and user impact
• Perform data analysis and build proof-of-concept to explore and propose ML solutions to both new and existing problems
• Develop statistical, machine learning, or optimization models
• Write production quality code to launch machine learning models at scale
• Evaluate machine learning systems against business goals