Principal Software Engineer

Maintain and improve the Flawless platform : improving existing functionality and adding new ones at very quick pace, going from suggestion to production in a matter of days

Develop new features using innovative tools: you will need to look into potential components, test them, and integrate AI tools and other technologies directly into the platform.

Work across the entire stack : Push into the layers most engineers don't — media pipelines, durable workflows, distributed systems internals — to unlock things that aren't possible at the app layer alone.

Research and keep yourself up to date: constantly look at what is on the market and where the technology frontier is, sharing your findings with the team and coming up with innovative ideas for improving the platform

Shape the architecture : Bring an engineering point of view to how the platform grows — what we build, in what order, and why.

Have built large-scale SaaS platforms from scratch — making the foundational decisions and living with them — not just joined a mature codebase, and can point to systems you owned end to end.

Have shipped products to real customers, dealt with user feedback and with the technical challenges of scaling.

Worked on large monorepo-based projects using leading web technologies, such as Typescript/Javascript with modern frameworks (React/Vue/Angular) and Python.

Understand the abstractions you build on, not just the API surface — you know what's happening a layer or two down, and you can reason from first principles when the abstraction leaks.

Care about quality while keeping in mind deadlines and priorities.

Developed media-specific platforms, such as CDNs, media ingestion pipelines, editing tools, etc.

Experience integrating AI into production systems, not just with chat interactions, but using vendor APIs and managing permissions, costs, different models and vendors

Experience with DevOps, managing infrastructure and developing CI/CD pipelines

Have real depth below the abstraction layer — at least one low-level language (C, C++, Rust, Zig, or equivalent) — and it informs how you build above it.

Most AI tools never leave the demo. Ours can't hide — they're used by expert teams who notice every miss, against a real P&L, all day, every day. We're a small, senior group of scientists and veteran engineers from leading tech and consumer companies, and we hire deliberately for people who want hard problems, real users from day one, and room to own things end to end.

We work in tight loops: an idea can go from a prototype to a product in front of operators and clients in days. We start with unique leverage — proprietary data and the industry-leading playbook behind billions in ad spend — build the tools in-house, prove them in production at massive scale, and then ship the winners beyond TubeScience. Velocity beats perfection until something earns the right to scale.

TubeScience Labs is the applied-AI team inside TubeScience, headquartered in Los Angeles. You'll join a small, senior group with an outsized surface area: real autonomy, a one-of-a-kind dataset, and a direct line from your code to real customers.

We offer competitive compensation, comprehensive benefits, plus generous access to frontier and open-weight models for day-to-day work, prototyping, and evals. Most of all, we offer the rare thing in applied AI: hard problems, expert users from day one, and the room to take an idea from prototype to shipped product. Come build at the frontier with us!

We encourage you to apply even if you don't believe you meet every single qualification. Not all strong candidates will check every box as listed, and the best people we've hired rarely did. If this work excites you and you think you could do it well, we'd rather hear from you than have you rule yourself out — so please submit an application.