> Markdown version of [/jobs/ext/3003559-research-engineer-qc-automation](https://www.wearedevelopers.com/jobs/ext/3003559-research-engineer-qc-automation). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Research Engineer, QC Automation - **Company:** Dreams 2 Reality Recruitment LLC - **Location:** San Francisco, CA, United States - **Salary:** $100,000.0 - $200,000.0 - **Contract:** Permanent contract - **Skills:** Training Data, Artificial Intelligence, Automation of Tests, Software Debugging, Python (Programming Language), Linux System Administration, Large Language Models, Build Tools, Docker - **Published:** September 19, 2026 - **Apply:** https://www.wayup.com/i-j-Research-Engineer-QC-Automation-Dreams-2-Reality-Recruitment-633363257867672/ ## About the Role Experience: Technical aptitude and learning potential matter more than years of experience., + Strong proficiency in Python, Docker, and Linux environments. + Excellent judgment about what constitutes good data and how to measure it. + Genuine curiosity about unfamiliar domains, with the ability to ask the right questions to develop a deep understanding quickly. + Experience building scalable data-validation pipelines, automated QA/QC systems, or similar infrastructure without a prescribed roadmap. + Experience designing or working with benchmarks and evaluations. + Comfort working in an early-stage startup environment , taking ownership and executing independently. + A track record of learning quickly and tackling problems that don#39;t come with clear instructions. Strong Signals + Knowledge of statistics and experimental design. + Strong written and verbal communication skills. + Comfort designing metrics, experiments, and QA/QC processes. + Ability to construct tasks for new evaluations and benchmarks. + Comfort operating in unstructured problem spaces. + A tendency to dig into the underlying problem rather than reaching for the first available tool or solution. ## Description HUD builds infrastructure for companies creating training data for AI agents. As demand grows, we need robust systems that can maintain and scale data quality. As a Research Engineer, QC Automation , you'll build the systems that make that possible. You'll develop automated quality-control infrastructure grounded in human judgment and a deep understanding of what makes training data useful-not simply by relying on LLMs to judge other LLMs. This is a highly autonomous role for someone who enjoys ambiguous problems, learns quickly, and can turn unclear quality requirements into measurable, scalable systems. What You'll Do + Build quality-control systems grounded in human judgment and a deep understanding of data quality, with limited reliance on LLM-based evaluation. + Define, formalize, and enforce quality standards for training data. + Design experiments, benchmarks, and metrics to evaluate agent performance. + Partner with data vendors to identify agent failure modes , debug quality issues, and improve data-generation processes. + Build systems for auditing supplier datasets , including sampling strategies, rule-based validation, model-assisted validation, and feedback loops. + Integrate QC insights into HUD's infrastructure and data-vendor portal to reduce anomalies, inconsistencies, and edge cases. + Work across unfamiliar domains and turn loosely defined quality problems into reliable, repeatable processes. ## Related Videos - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Fireside Chat: Deep Learning, Deep Impact: Harnessing AI for Language Innovation](https://www.wearedevelopers.com/videos/612-fireside-chat-deep-learning-deep-impact-harnessing-ai-for-language-innovation) - [Data Science, ML & AI in the Oil and Gas Industry at NDT Global - Dr. Katja Träumner](https://www.wearedevelopers.com/videos/1308-data-science-ml-ai-in-the-oil-and-gas-industry-at-ndt-global-dr-katja-traumner) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) - [How I Built QA from Scratch in a Scaling Startup - no fluff real life story](https://www.wearedevelopers.com/videos/2041-how-i-built-qa-from-scratch-in-a-scaling-startup-no-fluff-real-life-story) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Résumé-Driven Development: How IT trends affect the job market for software developers](https://www.wearedevelopers.com/magazine/59-resume-driven-development-how-it-trends-affect-the-job-market-for-software-developers) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Building AI Solutions with Rust and Docker](https://www.wearedevelopers.com/magazine/494-building-ai-solutions-with-rust-and-docker) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)