Careers · Noida, India
Help us teach industry to run itself.
wiseDo is building physical AI infrastructure for the plants that already exist: cameras that understand work, evidence an auditor can verify, and a platform that will eventually move real machines and robots. It is early, the problems are hard and physical, and everything you build ships to a real floor.
Open roles
We are hiring. We just don’t keep a list.
A team this size changes shape faster than a careers page can. Rather than post seats that are stale by the time you read them, here is the honest version: if you are good at any of the work below, write to us and we will make room. Every application is read by a person, and you will hear back either way.
Backend & platform
Event pipelines, edge-to-cloud sync, append-only stores, the governed APIs everything else rides on. Python and Postgres, mostly.
Computer vision
Detection, tracking and re-identification that has to hold up on a real plant’s cameras, in real lighting, for a model someone will be audited against.
Robotics & simulation
ROS 2, manipulation, fleet coordination, and turning a floor layout into a scene worth simulating against.
Solutions & sales
Floor walks with plant leaders, pilots scoped honestly, and long relationships with the people who run Indian manufacturing.
Product & design
Interfaces an operator will use on a noisy floor at the end of a shift, where a confusing screen is a safety problem.
Founder’s office
Product, operations, research and go-to-market alongside the founder. A front-row seat to building a deep-tech company.
Write to liveops@wisedo.in and tell us what you would build. Attach a CV if you have one, or link the thing you are proudest of — we would rather see the work.
Why here
The work is real.
Physical, not abstract
Your code decides what a camera is allowed to flag, what an auditor can verify and what a supervisor sees on a screen — on real floors, not in a demo environment.
Early with ownership
A small team where you own whole systems, not tickets. Decisions happen in days.
The long game
Every use case we solve deepens a machine-readable understanding of industrial work: the foundation for an operating system for the physical world.
People keep the judgment
We build for operators, not around them. Machines take the repetitive part; people do the part that needs judgment.