Machine Learning Engineer

Lyft is seeking a Machine Learning Engineer to design, build, and deploy ML systems across Lyft Business. The role involves working on pricing algorithms, fraud detection, agentic AI, and other ML applications. You will own models end-to-end and collaborate with cross-functional teams.

• Develop and deploy ML models across multiple problem domains including dynamic pricing, marketplace optimization, fraud detection, and anomaly/behavior detection.
• Build and iterate on agentic AI systems (e.g., LLM-powered analytical agents).
• Design and implement feature pipelines, model training workflows, and serving infrastructure.
• Partner with Data Scientists to take research prototypes to production.
• Evaluate ML system performance against business KPIs and run experiments.
• Identify new opportunities where ML can create leverage across Lyft Business verticals.
• Contribute to team engineering standards.

• Experience with GenAI/LLM ecosystems including prompt engineering, RAG, agent frameworks (e.g., LangChain, LangGraph), or fine-tuning.
• Exposure to graph-based ML methods (graph neural networks, knowledge graphs, network analysis).
• Experience with pricing, marketplace, or fraud-related ML problems.