Ando

• Run high-volume outbound to owner-operators and operations leaders at restaurant groups with 10 to 50 locations. • Lead demo calls that show prospects how Ando can help them forecast demand, improve staffing, and reduce schedule friction. • Close deals with urgency and ownership. • Manage pilots through paid conversion. Own the relationship from first call through renewal. • Work directly with the Head of Growth and leadership team on strategy, pipeline prioritization, and target accounts. • Bring customer feedback back to Product, Operations, and Customer Success so we keep building around real operator needs.

• You'll own our agile process and turn product priorities into execution plans engineering can actually deliver. • Run planning, standups, retros, and refinement efficiently, protect maker time, drive commitments to completion, and keep tuning the process as the team grows. • Keep engineering execution aligned with product priorities, from requirements through initiatives, projects, and shippable features. • Work across Product, Operations/Customer Success, and Go-to-Market to surface customer and business needs into priorities. • Keep leadership informed with clear weekly status and delivery metrics (velocity, cycle time, throughput). • Manage timeline and trade-off expectations, track cross-team dependencies, and escalate before risks become slips. • Run new-customer rollouts as projects across data integrations, backend, and frontend.

• You will own the design, development, and production deployment of Ando’s machine learning systems, including demand forecasting, labor allocation intelligence, and LLM-powered workflows. • This is a production ML role. You will work across the full data and ML lifecycle - from ingesting inconsistent real-world data to building reliable, continuously improving systems in production. • You will operate with high autonomy, make pragmatic modeling decisions, and build systems that directly impact real-world outcomes for businesses and workers. • This role is designed as a foundational technical leadership position, with meaningful influence over data architecture, model strategy, and system reliability. • Collaborate closely with Product, Engineering, and Operations to integrate ML into core workflows.