---
title: 'Software Development Engineer in Test (SDET) at Zefr'
canonical: 'https://feeny.ai/job/software-development-engineer-in-test-sdet-zefr-marina-del-rey-bq4tsag7sm4m'
type: 'job'
last_seen: '2026-10-16'
---

# Software Development Engineer in Test (SDET) at Zefr

- **Company:** Zefr
- **Location:** Marina Del Rey, CA
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-10-13
- **Last confirmed live:** 2026-10-16
- **Apply:** https://jobs.ashbyhq.com/zefr/2e63eeac-1d66-4cd2-b3c5-a40aaaf5e844

## Job description

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 servers) for correct behavior, input validation and error handling.
- Keep tests running in CI/CD. Wire suites into pipelines so they gate merges and deploys. Keep them fast and reliable by triaging failures, fixing flaky tests and cutting run time.
- Validate releases in preview, staging and production: prepare test data, run regression, sign off, and verify after deploy.
- Monitor production quality. Build synthetic checks, dashboards and alerts that catch regressions and bad data before customers do.
- Investigate issues and incidents. Reproduce problems, find root causes, write clear bug reports and verify fixes. Help out during high-severity incidents.
- Work across roles with engineers, product managers, data scientists and customer-facing teams. Turn findings into well-scoped tickets and share quality status openly.

What you bring:

- 1–3 years of experience, ideally as a QA engineer or SDET, with hands-on test automation.
- Solid coding skills in at least one language used for test automation. Python is preferred; Java, TypeScript or Go also work.
- Experience automating API tests: request and response validation, schema checks and negative cases.
- Experience with a modern UI end-to-end framework such as Playwright, Cypress or Selenium.
- Working SQL. You can query across tables to confirm data is complete and correct.
- Good test design instincts: edge cases, boundary values, negative cases and the test pyramid.
- Comfort with Git, pull requests, code review and running tests in CI/CD pipelines.
- Persistence when debugging: reading logs, inspecting network calls and querying databases.
- Clear written communication: bug reports, test plans and short async status updates.

Nice to have: None of these are required. If you have some of them, tell us.

- Exposure to a public cloud (GCP, AWS or Azure) and containers.
- Testing data pipelines and orchestration tools (Airflow, dbt, Great Expectations, Elementary) or data warehouses (Snowflake, BigQuery).
- Testing ML models or LLM-powered features, including evaluation datasets and handling non-deterministic outputs.
- Testing AI agents or MCP servers, or using AI coding assistants to speed up test writing and exploratory testing.
- Observability and alerting tools (for example Datadog, Grafana, Cloud Monitoring, PagerDuty) and synthetic monitoring.
- Performance and load testing (k6, Locust, JMeter).
- Experience with ad tech, digital media or large third-party platform APIs (Google Ads, Meta, TikTok, Snap).
- Frontend knowledge (React) to test framework upgrades and migrations.
- Security basics for test environments, such as managing secrets for test accounts.

Benefits (for US based employees):

- Flexible PTO
- Medical, dental, and vision insurance with FSA options
- Company-paid life insurance
- Paid parental leave
- 401(k) with company match
- Professional development opportunities
- 13 paid holidays off
- Summer Fridays (we leave early)
- In-office, hybrid, and fully-remote work options available
- In-office lunches and lots of free food
- Optional in-person and virtual events (we like to celebrate!)

Compensation (for US based employees): The anticipated salary for this position is between $90,000 and $120,000. Within the range, individual pay is determined by factors such as job-related skills, experience, and relevant education or training.

Zefr is an equal opportunity employer that embraces diversity and inclusion in the workplace. We are committed to building a team that represents a variety of backgrounds, skills, and perspectives because we know this only makes us better. We strongly encourage women, persons of color, LGBTQIA+ individuals, persons with disabilities, members of ethnic minorities, foreign-born residents, and veterans to apply even if you do not meet 100% of the qualifications.

## About Zefr

## Company Overview
- **One-liner**: Zefr provides AI-powered brand safety, suitability, and viewability technology for social media platforms, enabling advertisers to navigate content risk and unlock performance across the feed.
- **Entity Type**: Private (growth-stage, backed by venture capital)
- **Headquarters**: Los Angeles, California, USA
- **Founded**: 2008
- **Founders**: Rich Raddon and Zach James

## Core Business
- **Primary industry/industries**: AdTech, Marketing Technology, Brand Safety & Suitability, AI/ML Content Classification
- **Target customers**: B2B — Enterprise brands, agencies, and advertisers running campaigns on major social platforms (Meta, TikTok, YouTube, Instagram)
- **Mission or purpose statement**: To help marketers move confidently through the chaos of social platforms with technology built to decode the feed — enabling brands to "be fearless in the feed."

## Products & Services
- **Zefr Platform Intelligence**: A multi-modal content classification engine that ingests video, audio, imagery, text, and metadata to provide frame-level accuracy for brand safety, suitability, misappropriation, AI-generated content, and viewability.
- **Activate and Verify**: Programmatic activation and verification for social platforms, available both pre-bid and post-bid, connecting planning data with performance metrics.
- **Custom Policy Moderation**: In-house content policy practitioners define custom brand models and guidelines, with human review for validation and escalation.
- **Zefr Media Services**: A managed media team that runs campaigns end-to-end using Zefr’s proprietary data and technology.
- **Zefr Labs**: An innovation arm building intelligence for emerging platforms, including how brands show up in AI and new media environments.
- **Data Solutions**: Cross-platform data ingestion and classification for deeper video understanding.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed
- **Key Metric**: Total funding not publicly disclosed; revenue is private
- **Notable Investors/Partners**: Deep, direct integrations with Meta, TikTok, YouTube, and Instagram. Zefr was selected as the first third-party brand safety partner on both TikTok and Meta.
- **Growth Signals**: 
  - First third party to receive MRC accreditation for content-level reporting of brand safety and suitability on YouTube (2026)
  - MRC accreditation for viewability & IVT (2025), offered to advertisers free of charge
  - Expanded capabilities from YouTube (2008) to Facebook/Instagram (2015) to TikTok (2021)
  - Continues to build for AI and emerging platforms via Zefr Labs

## Competitive Advantages
- **Social-first architecture**: Engineered from the ground up to understand nuances of video, audio, and text within complex social feeds — not retrofitted from legacy open-web tools.
- **Platform-native partnerships**: Deep, direct integrations with major platforms ensure data accuracy and privacy compliance.
- **Independent intelligence**: Zefr is not a media owner, so its interests align purely with advertisers, providing unbiased data and insights.
- **Frame-level accuracy**: Multi-modal AI models trained for nuance, not keywords, enabling deep classification at scale.
- **First-mover accreditations**: First third-party MRC accreditation for content-level brand safety on YouTube (2026) and long-standing certifications.

## Strategic Focus
- **Current priorities**: Expanding content-level brand safety and suitability across all major social platforms; leading in viewability and IVT measurement; building intelligence for AI-generated content detection; and developing solutions for how brands show up in emerging AI platforms.
- **Growth direction**: Deepening platform integrations, scaling MRC-accredited metrics, and innovating through Zefr Labs to stay ahead of cultural and technological shifts in the social feed.

## Why Work Here
- **Culture highlights**: Zefr emphasizes a collaborative, inclusive environment with a focus on responsible marketing. The company values integrity, respect, and transparency — including a commitment to updating candidates at least once per week during the interview process.
- **Remote/hybrid/office policy**: Offers in-office, hybrid, and fully-remote work options.
- **Notable perks**:
  - Flexible Paid Time Off
  - Medical, Dental, and Vision Insurance with FSA Options
  - Company-Paid Life Insurance
  - Paid Parental Leave
  - 401(k) with Company Match
  - Professional Development Opportunities
  - 10 Paid Holidays
  - Summer Fridays (shorter work days on select Fridays during summer)
  - In-office lunches and free food
  - Optional in-person and virtual events, quarterly happy hours, team building, volunteer opportunities
- **Interview process**: Typically includes a Recruiter Phone Screen, Hiring Manager Interview, and Team Interview (with a coding challenge for technical roles). Goal is to provide a decision within three weeks or less.

## Sources
1. [zefr.com](https://zefr.com/about/company)
2. [zefr.com](https://zefr.com/)
3. [zefr.com](https://www.zefr.com/about/careers)
4. [zefr.com](https://zefr.com/about-us/culture)
5. [jobs.ashbyhq.com](https://jobs.ashbyhq.com/zefr)

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