Senior SWE, Machine Learning

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.

Data and Machine Learning are at the heart of Lyft’s products and decision-making. 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.

Responsibilities:

• 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.

 Experience:

• B.S., M.S. or Ph.D. in Computer Science, related technical field or relevant work experience
• 3+ years of industry or research experience developing ML models or infrastructure
• 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

Benefits:

• Great medical, dental, and vision insurance options
• Mental health benefits
• Family building benefits
• In addition to 12 observed holidays, salaried team members have unlimited paid time off, hourly team members have 15 days paid time off
• 401(k) plan to help save for your future
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• Pre-tax commuter benefits
• Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program

Lyft is an equal opportunity/affirmative action employer committed to an inclusive and diverse workplace. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Thursdays and a team-specific third day. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected range of pay for this position in the San Francisco Bay Area is $144,000 - $180,000. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Range is not inclusive of potential equity offering, bonus or benefits. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.