Staff Applied ML Engineer, Rider

Lime is the largest global shared micromobility business, operating in close to 30 countries. They are hiring a Staff Applied ML Engineer to own and evolve Lime’s CX Automation domain, responsible for improving customer support efficiency through automation.

Responsibilities:

• Own the technical direction and execution of Lime’s CX Automation platform, spanning self-service, AI-driven decision-making, and human-in-the-loop workflows
• Architect and build scalable backend systems that integrate internal APIs and third-party platforms to automate high-volume rider issues and reduce manual support effort
• Design and operate decision engines and automation workflows that take real actions (e.g. ending trips, issuing refunds) with clear guardrails for fraud, abuse, and rider trust
• Partner with Product and CX Operations to translate support policies and edge cases into executable automation logic, prioritizing work based on volume, cost impact, and risk
• Drive foundational platform investments (e.g., API coverage, workflow infrastructure, observability) required to scale automation reliably
• Measure and improve automation effectiveness using data

Requirements:

• 6+ years of professional software engineering experience with a track record of owning and operating production systems at scale
• Strong backend engineering experience building reliable, scalable services and APIs that support high-volume, customer-facing workflows
• Experience building applied AI or automation systems in production, including decision logic, workflow orchestration, or human-in-the-loop processes (deep ML research experience is not required)
• Demonstrated ability to set technical direction and drive multi-quarter initiatives, making sound architectural and tradeoff decisions in complex, ambiguous environments
• Proven judgment in designing systems with real-world constraints, including cost efficiency, operational risk, abuse prevention, and customer trust
• Clear and effective communicator who can collaborate across Product, Operations, and Engineering to solve business problems