About Bucket Robotics

At Bucket Robotics, we’re on a mission to revolutionize quality control in manufacturing. Today, over $10 billion worth of manufactured parts are scrapped due to defects, and traditional inspection methods are slow, expensive, and unreliable. We’re changing that by deploying AI-powered vision systems that detect defects faster, more accurately, and with minimal setup.

Our unique approach uses synthetic data generated from CAD models, allowing us to deploy defect detection models 50x faster than competitors—no need for thousands of real-world images.

We’re a team of engineers and innovators with backgrounds from Michelin, Uber ATG, Argo AI, and Stack AV, applying our robotics expertise to solve real-world manufacturing challenges. We’ve already secured enterprise customers in automotive and plastics, and we’re just getting started.

If you're excited about AI, robotics, and making a tangible impact on manufacturing, we'd love to hear from you!

Role Overview

Bucket Robotics is hiring a Forward Deploy Engineer to work at the boundary between our core engineering team and real manufacturing deployments. You’ll spend most of your time in San Francisco building alongside our engineers—but regularly travel to customer sites across the U.S. to deploy, debug, and harden our system in real production environments.

This role is ideal for an engineer who wants to see their work leave the laptop and show up on factory floors—integrating cameras, models, and workflows with real constraints, real operators, and real uptime requirements.

Responsibilities

• Deploy Bucket’s vision systems at customer manufacturing sites
• Work directly with customers during onboarding, pilots, and early production runs
• Integrate cameras, edge devices, and models into real production workflows
• Debug issues spanning software, ML models, hardware, lighting, and environment
• Serve as the technical owner for in-field issues from discovery through resolution
• Collaborate closely with the core engineering team to reproduce issues and ship fixes
• Translate real-world deployment pain points into actionable product and platform improvements
• Build deployment playbooks, checklists, and internal tooling to make future rollouts faster and more reliable
• Support technical evaluations alongside sales and leadership without being a sales role

Required Qualifications

• 2+ years experience in software engineering, robotics, systems, or field-facing engineering roles
• Strong programming skills in Python
• Comfortable debugging complex systems across hardware and software boundaries
• Experience working directly with customers in technical environments
• Enjoys wearing many hats and operating in fast-moving, ambiguous situations
• Willingness to travel ~30% of the time to customer sites across the U.S.

Preferred Qualifications

• Experience deploying or supporting ML or computer vision systems in production
• Familiarity with cameras, edge devices, or embedded systems
• Background in robotics, manufacturing, automation, or industrial environments
• Experience with Linux-based systems and on-prem or edge deployments
• Previous startup or early-stage company experience

What We Offer

• Competitive salary & meaningful equity – help shape how our technology works in the real world
• Comprehensive benefits – health, dental, and vision insurance
• Professional development budget – conferences, courses, and skills growth
• A chance to build something real – see your work running on factory floors across the country

Our Values

Innovation First: We solve hard, real-world problems in robotics and manufacturing

Ownership Mentality: We take responsibility from deployment through resolution

Customer Trust: We build systems customers rely on in production

Continuous Learning: Every deployment makes the product better

Bucket Robotics is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Tech at Bucket Robotics

At Bucket Robotics, we’re building AI-powered vision systems that solve real manufacturing problems—fast. Our stack is designed for rapid iteration, photorealistic synthetic data generation, and easy deployment to factory floors.

We work across the full stack of industrial AI:

AI & Vision

Custom computer vision models trained entirely on synthetic data generated from CAD—no real-world defects required.

Synthetic Data Generation

Blender-powered rendering pipelines with industrial materials, realistic lighting, and defect modeling, all configurable from the browser.

Edge Deployment

Models exported to ONNX and deployed on NVIDIA Jetson and x86 platforms for real-time inference on the line.

Manufacturing Integration

Outputs connect directly to manufacturing systems—ERP (SAP, Oracle, etc.), MES, and quality tracking—ensuring that inspection insights feed into production workflows.

Developer Experience

We build with Python, TypeScript, and WebGL (Three.js), using a modern stack (React 19, TailwindCSS, Vite, Flask) to maximize speed, usability, and flexibility.

We're solving the cold-start problem in machine vision with an engineer-friendly platform built for real production environments. If you care about closing the loop between CAD, QA, and deployment—let’s talk.