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First-time day at Zipline

Stop vehicles reading as open ground instead of loosening the planner

You’re the ai / ml engineer. Your team is in the room. Printed Oct 12, 2026.

Parked vehicles are producing delivery holds where the approach remains usable.

Faster first-approach completion pulls against preserving conservative obstacle interpretation near customer handoffs.

Who you’d be doing this for

“I’ve got orders loaded and customers asking for updates, but the aircraft keeps waiting at the same driveways.”

Gabriela Szymanski · Fulfillment Operations Manager

Oversees order staging and exception handling at a partner location where ready orders are delayed by mission holds.

What is at stake

Avoidable mission holds affect 8% of eligible deliveries at three busy locations. You have to weigh faster approach completion against conservative obstacle interpretation.

Why it isn’t already fixed

Every obvious fix costs something else. That’s the part you’d have to decide.

  • delivery throughput vs conservative obstacle behavior
  • richer scene understanding vs onboard compute limits
  • replay gains vs field representativeness
  • model correction vs planner thresholding

Why Zipline

Backyard delivery depends on the droid interpreting real customer driveways reliably within its onboard compute limits.

Written with these in mind

production perception engineerrobotics ML engineercomputer vision systems engineer

Not your kind of problem? 71 more at Zipline, or browse every organization.

This is the setup. The work is inside.

Running it puts you in the room: the full situation and its constraints, stakeholders who push back in their own words, and the decisions that are yours to make. What you produce becomes a Day One Plan — work you can show someone instead of describing.

Stop vehicles reading as open ground instead of loosening the planner — a live brief for Zipline