ZoomLogi

ZoomLogi

Full-Stack Engineer

San Francisco HQ · Exec

Sponsorship not specified$180k-$240kDetected 219 days ago
TypeScriptPythonReactFull-Stack DevelopmentCode ReviewKafkaMachine LearningLLMsIncident ResponseComplianceSupply ChainLogisticsHIPAA

About the role

  • The data ingestion and prediction layer.
  • The platform ingests a continuous stream from carriers, forwarders, IoT sensors, weather, and flight data, stitched into a unified low-latency picture of every active shipment.
  • We continuously scan for risk using ML and the mosaic view of each shipment to flag issues before they cascade.

Responsibilities

  • The compliance constraints, the quality/logistics tension, the fact that what you ship is moving medication to real patients: these should feel like compelling design constraints, not obstacles.
  • You'll be in customer calls regularly, because what you hear there will inform what you build.
  • You'll own meaningful product areas from idea to release and back again, working closely with the founding team.
  • Every new customer brings two or three of their own.
  • The most interesting problems here don't come with detailed specs: you hear something from a customer, you figure out what to build, and you build it.

Requirements

  • You have 2-7 years of professional engineering experience.
  • You have production experience, you've shipped software with real users, with tests, code reviews, and CI/CD.
  • You have a specific recent example of something you built, owned, and got in front of real users.

Benefits

  • Best-in-class medical and dental (100% self, 50% dependents)
  • Above market (4-year vesting, 1-year cliff)

Company info

  • Nobody calls a logistics coordinator to say things went well. They call because a $100,000 shipment of clinical trial medication has been sitting in customs for three days and nobody can explain why. Because a biologic therapy arrived outside its temperature window and the treatment has to start over. Because the patient is waiting and nobody in the supply chain can give a straight answer about the shipment's location.
  • This is the problem we're solving. We're a year in, tracking over 500,000 shipments (including for Fortune 100 customers), and we've already cut manual ops effort in half. General Catalyst, Eclipse Ventures, and Virtue led the seed. The angels are all former or current operators who've spent careers tracking down shipments themselves, such as Head of Logistics at Bristol Myers Squibb, CMO of Cardinal Health, President of Novo Nordisk US, President of UPS Air, and CEO of Uber Freight. They know the market is as large as the problem is broken.
  • What we've built works, and the most interesting problems are still ahead of us.
  • Olivier, Co-founder & CEO
  • Nobody calls a logistics coordinator to say things went well.
  • They call because a $100,000 shipment of clinical trial medication has been sitting in customs for three days and nobody can explain why.
  • Because a biologic therapy arrived outside its temperature window and the treatment has to start over.
  • Because the patient is waiting and nobody in the supply chain can give a straight answer about the shipment's location.
  • This is the problem we're solving.
  • We're a year in, tracking over 500,000 shipments (including for Fortune 100 customers), and we've already cut manual ops effort in half.
  • General Catalyst, Eclipse Ventures, and Virtue led the seed.
  • The angels are all former or current operators who've spent careers tracking down shipments themselves, such as Head of Logistics at Bristol Myers Squibb, CMO of Cardinal Health, President of Novo Nordisk US, President of UPS Air, and CEO of Uber Freight.
  • They know the market is as large as the problem is broken.
  • Founded by a team of operators with deep experience in Logistics Tech & Healthcare (Ex-Uber Freight GM + Airspace CRO), joined by rockstar engineers from the likes of Abbott, Uber, Hippocratic AI, BAM (Hedge fund), and others.
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This listing is sourced directly from ZoomLogi's careers page and normalized into a canonical job model.