Engineering Manager – Machine Learning Platform

At Lyft, our purpose is to serve and connect. To do this, we start with our own community by creating an open, inclusive, and diverse organization.

Lyft’s engineering team is growing rapidly, and we are looking for engineering managers to help us scale. Our engineers are smart, flexible, and love solving difficult challenges. They look to their managers for organizational transparency, career development, mentorship, and honest feedback. They move fast and ship code to production continuously, relying on their leadership to increase productivity by removing obstacles and keeping processes lean. Our engineering managers are people with varying technical backgrounds and interests -- some are involved in the technical details of their team and others provide general technical direction and oversight. As managers, our job is to keep teams efficient and executing on the right goals. We build teams that are inclusive, helpful, and have a strong sense of ownership for the things they build.

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 leaders to take on some of the most interesting and impactful problems in ridesharing.

As the Engineering Manager for the Machine Learning Platform team 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. 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:

• Lead the Machine Learning Platform team to deliver on multiple projects of increasing dependencies in an ambiguous or high-impact area
• Collaborate with other product teams on Marketplace like Pricing, Dispatch and Driver Earnings to ensure that the team is focused on the right problems
• Mentor and guide the professional and technical development of your team members. Help develop their careers, and assign them to projects tailored to their skill levels, personalities, work styles, and professional goals
• Build teams that are collaborative, inclusive, and respectful of each other
• Provide continuous feedback, address underperformance, and recognize the individual strengths and contributions of your team members
• Create plans for prioritizing technical and resourcing challenges in your organization
• Maintain a balance between building sustainable, high-impact projects and shipping things quickly
• Instill a spirit of continuous improvement in the team’s code, architecture, and processes
• Work closely with the Lyft recruiting team to hire high potential candidates from diverse backgrounds
• Work with your engineers and product managers to maintain a prioritized backlog and create short term and long term goals
• Own your team’s deliverables and ensure we continue to ship scalable, highly-available products that delight our passengers and drivers

Experience:

• 1+ years of experience as an Engineering Manager
• You have a technical background and are able to contribute to planning and design discussions
• You are steadfastly focused on your customers, whether they are drivers, passengers, or other Lyft employees
• You have experience leading a team of engineers and guiding them through their career development
• You believe in building both teams and products that scale
• You enjoy working in a collaborative environment, and you’re committed to driving projects to completion creatively
• You can motivate and instill a strong sense of ownership in your team
• You have experience guiding teams through planning, prioritization, and execution of work
• You think ahead and build for the future

Benefits:

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

Lyft is an equal opportunity 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, Wednesdays, and Thursdays. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the San Francisco area is $193,600 - $242,000. 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.