Founding Engineer (Fullstack Engineer) at Bucket Robotics (S24)

$150K - $200K • 1.50% - 4.50%

Defect detection for manufacturing built from CAD and synthetic data.

San Francisco, CA, US

Full-time

US citizen/visa only

3+ years

Apply now

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!

About the role

Skills: Python, Distributed Systems, Software Architecture

Role Overview

Bucket Robotics is hiring a Founding Fullstack Engineer to architect and build our core platform from the ground up. You'll own the entire product stack that transforms CAD models into production-ready AI systems deployed on factory floors.

This role is perfect for an engineer who loves building reliable, scalable systems from scratch—and wants to see their code running on real production lines.

Responsibilities

Design and build services for managing model training, deployment, and telemetry
Architect systems that go from CAD → synthetic data → deployed defect detector
Optimize model serving for low-latency inference on Jetson-class devices
Build data pipelines and observability tools that give insight into deployed AI systems
Work closely with the CEO and core team to shape product and technical strategy

Required Qualifications

3+ years experience in backend, infrastructure, or systems roles
Enjoys wearing many hats
Strong programming skills in Python, TypeScript, and React
Experience designing scalable APIs, task queues, and service-based systems
Familiarity with containers, cloud infrastructure (AWS/GCP), and CI/CD
Solid understanding of performance profiling, observability, and debugging in production environments

Preferred Qualifications

Experience deploying ML models to edge devices or with ONNX/TensorRT
Experience working with 3D data formats (e.g. STEP, STL, glTF) or synthetic data generation
Experience working with 3D modeling tools like Blender or Three.js
Background in IoT, robotics, or computer vision infrastructure
Previous startup or founding engineer experience

What We Offer

Competitive salary & meaningful equity – shape the company and share in its success
Comprehensive benefits – health, dental, and vision insurance
Professional development budget – attend conferences, take courses, grow your skills
A chance to build something real – work with a great team of roboticists, helping expand tooling for manufacturing.

Our Values

Innovation First: We push the boundaries of what's possible in robotics
Ownership Mentality: We take responsibility and act like founders
Collaborative Spirit: We work together to solve complex challenges
Continuous Learning: We're always growing and improving

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

Technology

Tech at Bucket Robotics

Robots and Rust—what’s not to love?

At Bucket Robotics, we’re tackling real-world, high-impact problems in manufacturing with AI-powered vision systems. Our tech stack is built for speed, scalability, and reliability, enabling us to deploy defect detection models 50x faster than traditional approaches.

We work across the full robotics stack:

AI & Vision: Custom machine learning models trained with synthetic data from CAD, eliminating the need for massive real-world datasets. Edge Computing: Optimized NVIDIA Jetson deployments, running real-time vision algorithms directly on factory floors. Embedded Systems & Robotics: Custom hardware, low-latency processing, and industrial automation integrations. Enterprise Software: ERP (SAP, Oracle, etc.) integrations, ensuring manufacturing insights flow directly into production workflows. Scalability & Deployment: Containerized solutions for on-prem & cloud, built with Rust, Python, and C++ for performance and safety.

We're solving hard problems in robotics, AI, and industrial automation, building systems that bridge the gap between cutting-edge AI and real-world manufacturing challenges. If you're excited about machine vision, robotics, and pushing the limits of automation, let's talk!

Interview Process

Our goal is to make this process respectful, fast, and focused on real-world skills—not LeetCode tricks or busywork. We’re hiring a founding engineer, and we want to understand how you think, how you build, and how you operate under ambiguity.

1. Phone Screen (15 minutes)

A quick call with our founder to:

Introduce the company and what we’re building
Hear a bit about your background and goals
Answer any quick questions

This is mostly a vibe check and mutual context setter.

2. Systems Thinking Challenge (Take-Home, ~2–3 hours, due in 4 days)

We’ll give you a small, toy problem from our world (e.g. synthetic data, defect classification, deployment infra).

What we’re asking you to do:

Sketch a system design at a high level
Write some light pseudocode or skeleton code to show your approach
Estimate how long you’d need to implement a v1
Write 3–4 short paragraphs on limitations, edge cases, and how you’d improve it

This isn’t meant to be a full build or a test of perfection—it’s to see how you approach real problems, communicate tradeoffs, and reason about complexity.

3. Systems Thinking Take Home Review (20 minutes)

A conversation on the take home exercise to talk through:

the tradeoffs of the solution you designed
how you would approach the implementation

4. Culture & Collaboration Interview (45 minutes)

A conversation focused on:

How you’ve worked in small, scrappy teams
How you deal with ambiguity, shifting priorities, and failure modes
What you need in a teammate/founder to do your best work

We want to know: can you thrive in the chaos of an early-stage startup?

5. Programming Interview (45 minutes)

A hands-on technical session with an experienced engineer. We’ll walk through code together and talk about:

Code clarity and correctness
Problem-solving approach
Communication and collaboration in a technical setting

6. Final Decision

We’ll move quickly after interviews conclude. If we’re aligned, we’ll get you an offer and start onboarding. We want to build momentum and move fast—and we’ll respect your time throughout the process.