Robotics engineer intern

Voiceflow

Los Angeles (CA)

On-site

USD 28,000 - 41,000

Full time

14 days+
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Job summary

Warp is seeking a Robotics & Computer Vision Engineer Intern in Los Angeles. You’ll begin with computer vision for warehouse and logistics scenarios, then expand into robotics to automate the physical supply chain.

You’ll own end-to-end development, deploy in real environments, and collaborate across hardware and software teams with the aim of transitioning to a full-time role. We value grit, intensity, and an ownership mindset.

Qualifications

  • Strong in Python and CV fundamentals.
  • Experience with PyTorch or OpenCV is a plus.
  • Familiarity with object detection, segmentation, or tracking.
  • Interest in robotics and ROS; working with 3D vision is beneficial.
  • Side projects, research, or production-oriented builds count.

Responsibilities

  • Develop computer vision pipelines to detect and track pallets, people, and vehicles in warehouses.
  • Prototype and deploy robotics workflows including vision-guided manipulation.
  • Collect data, train models, and validate performance in real environments.
  • Collaborate with hardware and software teams to ship production-ready solutions.

Skills

Python
Computer vision
PyTorch
OpenCV
Object detection
Multi-object tracking
ROS
3D vision
Edge inference

Tools

ROS
PyTorch

Job description

Robotics & Computer Vision Engineer Intern

Los Angeles, CA | 3 Month Internship | Path to Full Time

Warp is building the technology layer for the physical world.

We're looking for a Robotics & Computer Vision Engineer Intern to help us bring AI into physical supply chain operations.

You'll start with computer vision, building systems that can understand what is happening inside warehouses, cross docks, and vehicles in real time.

From there, the scope expands into robotics.

We want to use vision, humanoids, and other robotic systems to automate more of the physical work across the supply chain.

This is a three month internship, but we're hiring with the intention of finding someone who can become a full time engineer at Warp.

We want someone with grit, intensity, and an if not me, then who? attitude.

Nothing is beneath you.

What you'll work on

Initially, you'll focus heavily on computer vision:

  • Detect and track pallets, cartons, people, forklifts, and vehicles.
  • Understand freight movement through warehouses and cross docks.
  • Build systems for object detection, segmentation, tracking, OCR, and multimodal vision.
  • Automatically verify freight counts, loading, unloading, and handoffs.
  • Connect vision data into Warp's shipment and operational systems.
  • Collect data, train models, deploy them, and improve them in real operating environments.

Then the work gets more physical.

You'll help us explore and deploy robotics across supply chain workflows, including:

  • Humanoid robots operating inside warehouses and cross docks.
  • Robotic systems for freight handling, scanning, sorting, loading, and unloading.
  • Vision guided manipulation and navigation.
  • Connecting robots to Warp's software so they understand what work needs to happen next.
  • Evaluating new robotics hardware and figuring out where it can actually create value.
  • Taking emerging robotics technology and making it work inside messy, real world logistics environments.

The goal isn't to build robotics demos.

The goal is to put robotics into production.

You own the system

Getting a model or robot to work once isn't enough. You'll own what happens when lighting changes, freight is blocked, a sensor fails, a robot encounters something unexpected, or the warehouse looks nothing like the test environment. You'll deploy what you build, watch it operate, figure out why it fails, and keep improving it.

The problem is yours until it works.

What we're looking for

We're looking for trajectory more than years of experience. You should be strong in Python and have experience with some combination of:

  • Computer vision
  • PyTorch
  • OpenCV
  • Object detection and segmentation
  • Multi object tracking
  • Vision language models
  • Robotics
  • ROS
  • Camera calibration
  • 3D vision or depth sensing
  • Edge inference
  • Robot perception, manipulation, or navigation

Side projects count.

Research counts.

Something you built because you couldn't stop thinking about making it work counts.

More importantly, you:

  • Move extremely fast.
  • Like building in the real world.
  • Aren't afraid of hardware, messy data, or imperfect environments.
  • Figure things out without waiting for instructions.
  • Debug instead of making excuses.
  • Care about whether the system actually works in production.
  • Will mount cameras, label data, move equipment, test hardware, write code, or crawl around a warehouse if that's what solving the problem requires.
The environment

Warp is intensely meritocratic.

Responsibility isn't determined by experience, tenure, or title. It's earned by what you can own and deliver.

If you're exceptional, your scope can grow extremely quickly.

You may start with a vision model and end up owning how Warp deploys robotics across an entire part of the network.

If you're looking for a robotics internship where you spend three months optimizing something in simulation that never leaves the lab, this probably isn't it.

The three months

We're not giving you an intern project.

We want you working on real systems.

Over three months, we want to see whether you can build, experiment, deploy, solve physical problems, learn incredibly quickly, and earn increasing responsibility.

If you can, our goal is for this to turn into a full time engineering role at Warp.

Why Warp

Supply chains are still filled with physical work that software alone can't automate.

That is changing.

Computer vision can make the physical network observable. Robotics can make it programmable.

Warp already connects the shipments, warehouses, carriers, drivers, trucks, and software.

We want to build the intelligence and robotics layer on top of that network.

Start by teaching it to see.

Then help us teach it to act.

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