Machine Learning Platform Software Engineer, Lyft

• B.S., M.S., or Ph.D. in Computer Science and experience in distributed systems and machine learning
• Passion for building scalable and extensible solutions for machine learning development and productionisation towards short term and long term business and user impact
• Proficiency in Python, Golang, or other programming language
• Excellent communication skills and fluency in English
• Strong understanding of Machine Learning fundamentals, including supervised learning, forecasting, recommendation systems and reinforcement learning
• Experience with distributed computing frameworks and open source solutions such as kubernetes

Desirable

• As a member of the Machine Learning Platform team, you will work in a dynamic environment, where we embrace moving quickly to build the world’s best transportation network
• Machine learning infra engineers build systems that empower machine learning models to make our products predictive, personalized, and adaptive
• We’re looking for passionate, driven engineers to take on some of the most interesting and impactful problems in ridesharing
• As a machine learning platform engineer, you will be developing our central machine learning platform that powers Lyft machine learning and optimization models
• You will be working on a wide array of challenges ranging from building the large language model framework, large scale distributed model training, sub millisecond real-time predictions at scale, automating machine learning model lifecycle, implementing model monitoring, enabling reinforcement learning and many more
• You will be working in a fast paced environment, tackling a diverse set of problems
• They collaborate across transportation, economics, forecasting, mapping, personalization, and adaptive control
• We are hiring engineers who can work with modelers across the company and build infrastructure to incorporate the rapid developing needs 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
• Partner with Machine Learning Engineers, Data Scientists, Software Engineers and Product Managers to develop advanced systems for business and user impact
• Evaluate when to build and when to reuse existing components including open source solutions
• Write production quality code that scales with use
• Help establish roadmap and architecture based on technology and our needs