About the role
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.
With over half a billion rides and counting, Lyft is solving hard problems at scale, leveraging Machine Learning to better serve our customers. The Machine Learning Platform (MLP) team is seeking a backend Software Engineer to help build and operate our platform, which supports real-time, online, and offline ML model execution, development, and iteration across Lyft. In this role, you will own well-defined tasks and contribute to features alongside a team of highly motivated Machine Learning and Software Engineers, learning from senior engineers while shipping production code that impacts systems across the entire business.
If you are interested in hands-on exposure to classical machine learning models and production ML systems at scale, with applications across each facet of the marketplace and business, we are searching for you.
If you are a creative and critical thinker with an interest in machine learning systems, eager to learn and grow as an engineer, and passionate about solving business problems using data in a dynamic, creative, and collaborative environment, we are searching for you.
Responsibilities
- Own well-defined tasks and contribute to features on the ML platform, seeking guidance from senior team members when needed
- Develop reliable, performant, well-tested, readable, maintainable code that follows team coding standards and meets feature requirements
- Participate actively in code reviews, both giving and receiving feedback
- Monitor the stability and performance of your code after deployment, and proactively fix bugs and debug issues within your scope
- Participate in the team's operational responsibilities, including on-call rotations and following through on postmortem action items
- Contribute to technical debt reduction and technology modernization efforts
- Write documentation for the code and tasks you work on, including runbooks where needed, and help improve onboarding materials
- Participate in postmortems and planning discussions, providing input and feedback
- Collaborate with cross-functional partners, including the Machine Learning Engineers and Data Scientists who build on the platform
- Build your understanding of the ML platform and the tradeoffs behind its design by working closely with senior team members
- Utilize AI tooling to accelerate development workflows.