Research Engineer (AI)

TL;DR

Research Engineer (AI): Building QA infrastructure and validation pipelines for RL training data for frontier AI agents with an accent on data quality standards and scalable auditing workflows. Focus on designing model-assisted validation pipelines, optimizing human-in-the-loop review, and integrating QA metrics into infrastructure tools.

Location: On-site in the San Francisco Bay Area. Support for relocation and visas to the US provided for strong candidates.

Company

hirify.global builds infrastructure to create RL training data and evaluations for frontier AI agents, including a marketplace for frontier labs.

What you will do

• Define and enforce quality standards for AI training data.
• Build tooling and workflows to audit supplier-generated datasets, including sampling strategies and validation pipelines.
• Design and optimize human-in-the-loop review workflows for QA.
• Partner with data vendors to debug quality issues and improve generation processes.
• Integrate QA learnings into infrastructure tools and the data vendor portal.

Requirements

• Proficiency in Python, Docker, and Linux environments.
• Experience working with large-scale datasets.
• Must be based in or able to relocate to the San Francisco Bay Area.
• Startup experience in early-stage technology companies with the ability to work independently.
• Familiarity with current AI tools and LLM capabilities.
• Strong communication skills for remote collaboration across time zones.

Nice to have

• Understanding of common failure modes in training data.
• Experience building data validation pipelines or human-in-the-loop systems.
• Ability to design metrics, experiments, and QA processes.

Culture & Benefits

• Comprehensive medical, dental, and vision insurance (Blue Shield of CA).
• 401k, commuter benefits, and Equinox membership.
• Daily lunch and dinner provided in the office.
• Company-wide holiday break from Christmas Eve to New Year’s Day.
• Unlimited access to AI tokens for ChatGPT, Claude Code, and Cursor.

Hiring process

• Two technical interviews.
• One-week work trial.