Software Development Engineer in Test (SDET)

🏢 Zefr · 📍 Marina del Rey, CA · 💼 hybrid · ⏰ FullTime

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Position Summary & Responsibilities

What we do:

Zefr is the leader in AI-powered content classifications for brands and advertisers. Zefr’s platform is purpose built for multi-modal content understanding on open platforms like YouTube, TikTok, Meta and Snap, with pre-bid activation and verification solutions. Our products safeguard media and AI investments, while maximizing performance and efficacy on those channels.

Headquartered in Los Angeles with global offices across New York, Chicago, London, Toronto, Singapore, and more, Zefr is redefining what trust and transparency means for social media in the age of AI.

What you'll do:

We're hiring a Software Development Engineer in Test (SDET) with 1–3 years of experience to help own quality across our APIs, web apps, data pipelines and AI-powered services, mainly by writing code rather than running manual test scripts.

You'll work inside product engineering teams. You'll decide what to test and how, build and maintain automated tests in a shared framework, and make sure those tests gate every release. You'll also watch production through monitors and alerts.

This role suits an engineer who treats testing as a software problem and enjoys finding where systems break. That includes data and model outputs, not only screens and endpoints.

Plan testing for each feature. Join grooming, ask clarifying questions, and write test plans that cover happy paths, edge cases and negative cases.
Build and maintain test automation for REST and GraphQL APIs, backend services, web UIs and third-party partner APIs, in a shared code-based framework. Review teammates' test code.
Validate data pipelines and data quality. Write checks on pipeline outputs (schemas, row counts, freshness, business rules) and help define data SLAs.
Test AI and ML features. Compare model or prompt versions on fixed datasets, validate shadow deployments before rollout, and test AI agents and their tools (such as MCP

🎯 Candidate Preparation Guide For Zefr Applicants

Key Role Competencies & Evaluation Highlights

Key Role Focus:

Measuring programmatic advertising brand safety expertise, machine learning classification accuracy, and massive dataset handling.

📋 Preparation Priorities (Key Areas to Clarify):

1. Displaying ignorance of current privacy regulations like GDPR, CCPA, and cookie deprecation
2. Confusing basic audience targeting with advanced contextual content understanding
3. Inability to handle massive scale and low-latency processing requirements in ad-tech

✨ Recommended Role Alignment Hook:

I protect brand equity at scale by developing advanced contextual ML classifiers that navigate complex ad-tech ecosystems safely.

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