Senior Software Engineer, Forecasting & Real-Time Optimization
About The Position
The Senior Software Engineer will join Lyft’s Forecasting and Real-Time Optimization Platform (FORTOP) team in the Rideshare Experience & Marketplace organization. FORTOP provides reliable, real-time marketplace supply and demand signals and forecasts that support important products and automated business decisions, including Dynamic Pricing, Real-Time Supply Management, Fulfillment, and Driver Incentives. The engineer will lead the design and operation of production systems that transform streaming marketplace data into accurate, reliable forecasts. These systems include real-time feature pipelines, model training and inference infrastructure, backtesting and evaluation tools, and signal-serving layers used continuously by downstream products. The role partners with scientists to move models from prototype to production and collaborates with downstream teams to establish interfaces, data contracts, and reliability guarantees. Forecasting covers rider demand and driver supply as they change with traffic, holidays, and major events, with an emphasis on maintaining system correctness and performance during peak periods. Lyft describes its work environment as inclusive and collaborative. This role follows a hybrid schedule, with employees expected to work in the office three days per week on Mondays, Wednesdays, and Thursdays, and flexibility to work from anywhere for up to four weeks per year.
Requirements
- At least 5 years of industry software engineering experience, including building and operating production backend or data systems.
- A BS/MS or equivalent in Computer Engineering, Computer Science, or a related field, or relevant work experience.
- Experience designing and leading delivery of large-scale distributed systems and owning their reliability through monitoring, on-call, and incident response.
- Solid distributed-systems fundamentals, including fault tolerance, delivery semantics, and consistency tradeoffs.
- A track record of leading ambiguous, multi-engineer projects and mentoring other engineers.
- Clear written communication skills, including the ability to write design documents that align stakeholders.
Nice To Haves
- Experience building production machine-learning models and infrastructure, including model choice, feature engineering and pipelines, training and inference pipelines, model serving, or ML platforms.
- Hands-on experience with stream or large-scale batch processing (such as Flink, Beam, or Spark) and distributed messaging (such as Kafka or Kinesis).
- Experience with time-series forecasting systems or familiarity with backtesting and forecast evaluation, including error metrics, bias, and calibration.
- Experience with online experimentation or real-time decision systems such as pricing, dispatch, or marketplace balancing.
- Comfort using AI-assisted development tools to move faster without compromising quality.
Responsibilities
- Lead multi-engineer projects from proposal and technical design through launch; break work into milestones, align dependencies with partner teams, and own estimates.
- Design and evolve streaming feature pipelines, model training and inference workflows, and signal-serving systems, leading design reviews focused on latency, correctness, scalability, and cost.
- Reduce system complexity by consolidating or sunsetting components.
- Partner with scientists to design and productionize machine-learning models.
- Build rollout tooling, including shadow, canary, and rollback capabilities, as well as backtesting and experimentation infrastructure.
- Define and maintain interfaces, data contracts, and SLAs between forecasting signals and downstream consumers.
- Monitor system health and signal quality, prepare systems for peak events, participate in on-call, lead post-incident investigations, and complete follow-up actions.
- Write well-tested, maintainable code; conduct code reviews; and coach teammates on testing and engineering practices.
- Collaborate with Product, Science, and partner engineering teams to frame problems, shape the roadmap, and balance accuracy, latency, and complexity.
- Mentor engineers, participate in hiring and onboarding, and share knowledge through design documents, runbooks, and tech talks.
Benefits
- 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 with company match.
- Twelve observed holidays and paid time off: salaried team members receive discretionary paid time off; hourly team members receive 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.
- In-office perks.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
