# Lead Research Engineer, Data Quality

**Company:** [hud](https://hotfix.jobs/companies/hud)
**Location:** San Francisco, CA
**Role:** ML Engineering
**Experience:** 7+ years
**Skills:** Python, Docker, Linux, qc systems, evals, benchmarks, synthetic data pipelines, validation workflows, model evaluation infrastructure
**Posted:** 2026-07-28

> Lead the data quality team at HUDHUD to build QC systems, validation methods, and experiments that measure and improve training data for frontier AI agents and RL environments. Requires deep data quality intuition, Python/Docker/Linux proficiency, and experience turning research insights into production evaluation pipelines.

## Job Description

## Responsibilities
- Lead HUD’s data quality strategy including building QC systems, defining and enforcing quality standards, and designing experiments to grade agent outputs
- Develop new methods for validating synthetic data at scale, such as failure-mode analysis, task mutation checks, and trajectory auditing
- Partner with research engineers, domain experts, and data vendors to diagnose quality issues and improve data generation workflows
- Turn qualitative research insights into production systems, internal tools, dashboards, validation pipelines, and feedback loops
- Help build internal research taste around what makes agent training data actually useful, not just superficially correct
- Mentor other research engineers to maintain a high bar for technical rigor, clarity, and execution speed

## Requirements
- Advanced proficiency in Python, Docker, and Linux environments
- Deep intuition for data quality - you can reason about what makes tasks realistic, learnable, diverse, reliable, and useful for training
- Experience building QC systems, evals, benchmarks, synthetic data pipelines, validation workflows, or model evaluation infrastructure
- Comfort working across messy human and technical systems, including domain experts, vendors, generated data, model outputs, graders, and infrastructure
- Strong written communication and the ability to explain methodology clearly to researchers, engineers, labs, and external audiences

## Nice-to-Haves
- Experience leading teams on ambiguous technical projects from problem definition through implementation and iteration
- Experience working with subject-matter experts to capture domain judgment and convert it into scalable review or generation systems
- Be comfortable designing metrics, experiments, and QA/QC processes, not just executing them
- Early-stage startup experience with ability to work independently in fast-paced environments
- Be detail-oriented and able to spot subtle inconsistencies or edge cases in data

## Similar roles

- [Senior Applied ML Engineer](https://hotfix.jobs/jobs/0c6887b5-b731-427b-824c-4cfe3e62b39f) - Upstart - Remote - $159k – $232k/yr
- [Sr. Software Engineer](https://hotfix.jobs/jobs/73920675-e617-4e69-befa-3512f956d9f2) - Dialpad - San Francisco, CA - $225k – $252k/yr
- [Senior Systems Engineer](https://hotfix.jobs/jobs/2e412edb-bd7e-41b5-8a5b-d118f0c7e916) - Cloudflare
- [Senior Software Engineer, Perception](https://hotfix.jobs/jobs/71f62d57-4164-499b-a446-3913c581e93c) - Shield AI - Washington, DC - $163k – $245k/yr
- [Lead Data Scientist](https://hotfix.jobs/jobs/2ff620e8-618b-401a-b2e4-73820695a7b9) - Apartment List - Remote - $161k – $230k/yr

**Apply:** https://hotfix.jobs/jobs/ac0f34d5-3f0d-4735-b26d-b3addf4b75cc
**Canonical:** https://hotfix.jobs/jobs/ac0f34d5-3f0d-4735-b26d-b3addf4b75cc