Responsibilities

Lead projects end to end: Drive multi-engineer projects from proposal and technical design through launch. Break work into milestones, align dependencies with partner teams, and own estimates.
Architect ML systems: Design and evolve streaming feature pipelines, training and inference workflows, and signal serving, and lead design reviews with attention to latency, correctness, scalability, and cost. Reduce complexity by consolidating or sunsetting components.
Partner with science to ship: Partner with scientists to design/productionize ML models. Build the rollout tooling (shadow, canary, rollback) and the backtesting and experimentation infrastructure that make launches safe and fast.
Own signal contracts: Define and maintain the interfaces, data contracts, and SLAs between forecasting signals and downstream consumers such as Dynamic Pricing and Driver Incentives.
Operate what you build: Monitor system health (latency, freshness, error rates) and signal quality (accuracy, bias, drift), and prepare systems for peak events. Take part in on-call, lead post-incident investigations, and drive action items to completion.
Code quality: Write well-tested, maintainable code and give code reviews that improve the work of others. Coach teammates on testing and engineering practices.
Collaborate across functions: Work with Product, Science, and partner engineering teams to frame problems, shape the roadmap, and make clear tradeoffs between accuracy, latency, and complexity.
Grow the team: Mentor engineers, take part in hiring and onboarding, and share knowledge through design docs, runbooks, and tech talks.
5+ years of software engineering industry experience, including building and operating backend or data systems in production
BS/MS or equivalent in Computer Engineering, Computer Science, or 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: fault tolerance, delivery semantics, and consistency tradeoffs

Senior Software Engineer, Forecasting & Real-Time Optimization at Lyft · LumiJobs

Senior Software Engineer, Forecasting & Real-Time Optimization

Responsibilities

Benefits

Company

Lyft

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