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.

 We are seeking a talented Software Engineer to join our dynamic Streaming Compute Team. In this role, you'll be instrumental in designing, developing, and maintaining our low latency and high throughput systems, which are critical to almost all ML models at Lyft. Our systems are used to generate, store and serve ML features for training and inference for teams like payments fraud, driver and rider incentives, mapping etc. We also leverage our vector store to empower other use-cases using LLMs.

As a Software Engineer, with your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance the platform offerings. Your work will have a major impact on several areas of the business.

We are looking for candidates who are self starters and have a proven track record of delivering software solutions that can solve critical business needs. The candidate should be able to dive deep into any problems with lots of ambiguity and build a technical solution to solve it. They should be willing to take ownership of a project or a feature and be able to drive it from design to implementation.

• Design, develop, deploy, monitor, operate and maintain scalable and robust systems to support ML feature storage and retrieval
• Work with technologies such as Redis, dynamoDB, OpenSearch etc. to enhance our data platform's capabilities
• Collaborate with cross-functional teams to integrate feature service solutions into the broader data architecture
• Analyze our internal systems and processes and locate areas for improvement/automation
• Collaborate with product org stakeholders to address and prioritize custom edge cases
• Help lead large projects from inception to positive execution

• 5+ years of experience with building, deploying and maintaining low latency, high throughput services
• 5+ years of experience building and developing large-scale infrastructure, distributed systems or networks, and/or experience with compute technologies
• 3+ years of software engineering industry experience and with storage technologies like DynamoDB, Redis, Open Search etc.
• Experience working with kubernetes and container technologies (e.g. Docker, cri-o, etc)
• Familiar with a cloud-based environments such as AWS/GCP/Azure

• 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.  

Starting in September 2023, 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.

The expected range of pay for this position in the San Francisco Area is $139,500 - $155,000. 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.