13 hours ago
Base Salary
$148k - $185k/yr
Responsibilities
- Lead multi-engineer projects from proposal and technical design through launch, including milestones, dependencies, and estimates.
- Design and evolve streaming feature pipelines, ML training and inference workflows, and signal-serving systems for latency, correctness, scalability, and cost.
- Partner with scientists to productionize ML models and build shadow, canary, rollback, backtesting, and experimentation tooling.
- Define and maintain interfaces, data contracts, and SLAs between forecasting signals and downstream consumers.
- Monitor latency, freshness, error rates, accuracy, bias, and drift; participate in on-call and lead post-incident investigations.
- Write maintainable, well-tested code, conduct code reviews, mentor engineers, and promote strong testing and engineering practices.
- Collaborate with Product, Science, and engineering teams to shape roadmaps and balance accuracy, latency, and complexity.
- Contribute to hiring, onboarding, design documentation, runbooks, and technical talks.
Requirements
- At least 5 years of software engineering industry experience, including building and operating backend or data systems in production.
- Bachelor’s or master’s degree, or equivalent relevant work experience, in Computer Engineering, Computer Science, or a related field.
- Experience designing and leading large-scale distributed systems and owning their reliability through monitoring, on-call, and incident response.
- Strong fundamentals in fault tolerance, delivery semantics, and consistency tradeoffs.
- Experience leading ambiguous, multi-engineer projects and mentoring other engineers.
- Clear written communication skills, including the ability to create design documents that align stakeholders.
- Preferred experience with production ML models and infrastructure, including model selection, feature engineering, training and inference pipelines, model serving, or ML platforms.
- Preferred experience with stream or large-scale batch processing such as Flink, Beam, or Spark, and distributed messaging such as Kafka or Kinesis.
- Preferred experience with time series forecasting, backtesting, forecast evaluation, online experimentation, or real-time decision systems.
- Preferred comfort using AI-assisted development tools while maintaining quality.
Benefits
- Medical, dental, and vision insurance options with additional programs for enrolled members.
- Mental health, family building, child care, and pet benefits.
- 401(k) plan with company match.
- Twelve observed holidays and paid time off, with salaried team members receiving discretionary PTO and hourly team members receiving 15 days.
- Eighteen weeks of paid parental leave for biological, adoptive, and foster parents.
- Subsidized commuter benefits, monthly Lyft credits, and complimentary Lyft Pink membership.
- Hybrid schedule requiring in-office work three days per week on Mondays, Wednesdays, and Thursdays, with flexibility to work from anywhere for up to four weeks per year.
Tech Stack
Categories
About Lyft
Lyft is a NASDAQ-listed transportation marketplace that connects riders with drivers and offers bike and scooter rentals in one app. Founded in 2012 and headquartered in San Francisco, it operates across the U.S. and parts of Canada. Its revenue comes from service fees on rides and rentals, enterprise programs, and consumer subscriptions such as Lyft Pink.