hud Logo

hud

Research Engineer, QC Automation

Reposted 3 Months Ago
Be an Early Applicant
In-Office or Remote
2 Locations
100K-230K Annually
Mid level
In-Office or Remote
2 Locations
100K-230K Annually
Mid level
Build scalable QC systems and validation pipelines for RL training data: define quality standards, design metrics and experiments, audit supplier datasets, partner with vendors to diagnose failures, and integrate learnings into infrastructure and vendor tooling.
The summary above was generated by AI
About HUD

HUD's mission is to build reliable, fair and open infrastructure for AI data. We want data to be valuable for the people who create it and trustworthy for the labs that train on it. Our team is a quickly growing group of researchers, engineers and operators building the economy that shapes what AI will become. Backed by $16M from top VCs and YC (W25), our marketplace and platform are used by startups, Fortune 500 companies and frontier labs.

About the role

We're looking for Research Engineers to automate QC for training data created by companies using HUD’s infrastructure. You’ll build the systems that scale quality to help us meet our continued strong demand.

Responsibilities
  • Create QC systems based on true understanding and human judgement, without relying heavily on LLMs

  • Define and enforce quality standards for training data

  • Design experiments and metrics to grade agent outputs

  • Partner with data vendors to debug quality issues and diagnose agent failure modes, provide actionable feedback, and improve their data generation processes

  • Translate QC learnings into systems for auditing supplier-generated datasets, including sampling strategies, validation pipelines (rule-based and model-assisted), and feedback loops

  • Continuously integrate QC learnings into infrastructure tools and data vendor portal to reduce anomalies, inconsistencies, and edge cases

Experience

You may be a good fit if you have:

  • Proficiency in Python, Docker, and Linux environments

  • Strong understanding of what “good data” means and how to measure it

  • Genuine curiosity of different domains and great at asking questions to understand them

  • Built scalable data validation pipelines and automated QA/QC systems end-to-end without a fully prescribed roadmap

  • Experience working on benchmarks and evals - you can reason about what makes a task realistic, a rubric reliable, an environment usable, and a trajectory useful for RL training

  • Early-stage startup experience with ability to work independently in fast-paced environments

Strong candidates may also:

  • Have knowledge of statistics

  • Have strong written and verbal communication skills for collaboration with our partners and team members across time zones

  • Be comfortable designing metrics, experiments, and QA/QC processes, not just executing them

  • Have experience with existing benchmarks and can reason about how to construct tasks in new evals

  • Thrive in unstructured problem spaces

We prioritize technical aptitude and learning potential over years of experience. Motivated candidates are encouraged to apply even if they don't meet all criteria.

Team & company details
  • Team Size: ~25 people currently, mostly full-time in-person, but some remote.

  • Our team: Our team brings together five International Olympiad medalists across IOI, ILO and IPhO, researchers published at NeurIPS and ICLR, and engineers and researchers from Google DeepMind, Amazon, AWS, Meta, Qwen, GLM, and Mercor. It also includes operators from BCG and Uber, the first security hire at one of the largest crypto exchanges, serial AI startup founders, former quant researchers, artists and the former #1 ranked Catan player in the world.

  • Company stage: We have 8 figures in funding and are scaling profitably and quickly to meet very strong demand.

Logistics
  • Employment: Full-time.

  • Location: We have offices in San Francisco or Singapore but are open to remote candidates who can work hours that 70-80% overlap with either San Francisco or Singapore time zones.

  • Visa Sponsorship: We provide support for relocation and visas for strong full-time candidates to the US or Singapore.

  • Timeline: Applications are rolling. The process is 2 technical interviews and a 2-3 day work trial.

What we offer
  • Competitive compensation

  • 100% covered top-of-the-line medical, dental, and vision (US and Singapore employees)

  • Lunch and dinner for in-office employees

  • Company-wide holiday break (Christmas Eve to New Year’s Day) on top of PTO and paid holidays

  • 401k with a 4% match

  • Other perks including an Equinox membership and commuter benefits (US employees) and a health/wellness stipend (Singapore employees)

  • Unlimited* access to tokens for ChatGPT, Claude Code, Cursor, etc. *By unlimited, we mean no one on our token usage leaderboard has ever hit a limit. So we have no idea what the limit is.

  • Two top-floor offices in San Francisco’s Union Square and Singapore’s Raffles Place

  • Annual travel budget to visit either office

Compensation

Actual offers are adjusted for experience and location, but our base salary bands are

  • San Francisco (and other major US cities): $135,000 - $230,000

  • Singapore: $100,000 - $175,000

  • Rest of world: $100,000 - $175,000

Due to high volume, we may not actively respond to every application, but feel free to contact us at [email protected] or elsewhere if we missed your application!

Similar Jobs

4 Hours Ago
Remote or Hybrid
Senior level
Senior level
Fintech • Professional Services • Consulting • Energy • Financial Services • Cybersecurity • Generative AI
Leads end-to-end UI/UX and product design for digital wealth and AI-enabled products across web and mobile. Responsibilities include user research, journey mapping, information architecture, wireframing, prototyping, high-fidelity UI design, usability testing, design systems, and stakeholder collaboration. The role partners with product, business, engineering, and AI teams to create intuitive, accessible, technically feasible experiences and guide design delivery in Agile environments.
Top Skills: AgileAIDesign SystemsFigmaMobile ApplicationsWeb Applications
13 Hours Ago
Remote
Entry level
Entry level
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Troubleshoot, dismantle, repair, adjust, assemble, and rebuild electro-mechanical manufacturing equipment. Use diagnostic equipment to identify failures, follow blueprints and repair manuals, perform equipment checkouts, and modify equipment as directed by engineers. Apply AI-enabled tools to improve monitoring, troubleshooting, data analysis, productivity, and continuous improvement.
Top Skills: Ai-Enabled ToolsElectromechanical EquipmentTest And Diagnostic Equipment
2 Days Ago
Remote
Entry level
Entry level
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Develops, qualifies, deploys, and sustains semiconductor inspection and metrology solutions for advanced and conventional packaging. The role manages equipment qualification, lifecycle planning, tool matching, defect detection, yield improvement, data integration, dashboards, analytics, AI-enabled process control, NPI readiness, supplier collaboration, and cross-functional program execution.
Top Skills: Artificial IntelligenceAutomated WorkflowsDashboardsData Analytics PlatformsMrda Data SystemsSemiconductor Inspection And Metrology Systems

What you need to know about the Austin Tech Scene

Austin has a diverse and thriving tech ecosystem thanks to home-grown companies like Dell and major campuses for IBM, AMD and Apple. The state’s flagship university, the University of Texas at Austin, is known for its engineering school, and the city is known for its annual South by Southwest tech and media conference. Austin’s tech scene spans many verticals, but it’s particularly known for hardware, including semiconductors, as well as AI, biotechnology and cloud computing. And its food and music scene, low taxes and favorable climate has made the city a destination for tech workers from across the country.

Key Facts About Austin Tech

  • Number of Tech Workers: 180,500; 13.7% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Dell, IBM, AMD, Apple, Alphabet
  • Key Industries: Artificial intelligence, hardware, cloud computing, software, healthtech
  • Funding Landscape: $4.5 billion in VC funding in 2024 (Pitchbook)
  • Notable Investors: Live Oak Ventures, Austin Ventures, Hinge Capital, Gigafund, KdT Ventures, Next Coast Ventures, Silverton Partners
  • Research Centers and Universities: University of Texas, Southwestern University, Texas State University, Center for Complex Quantum Systems, Oden Institute for Computational Engineering and Sciences, Texas Advanced Computing Center

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account