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HUD

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  • HUD

    Delivery Engineer

    HUD · 🇺🇸 San Francisco, CA · posted 1 day ago
    ApplyFull posting

    Extracted from the posting

    Base
    $100,000 – $225,000
    Remote
    Remote: 70-80% hours overlap with SF or Singapore
    Funding
    8 figures in funding; $16M from VCs, YC W25
    Eng team
    ~25 people, mostly in-person, some remote
    Visa
    Relocation and visa support for US or Singapore
    Stack
    Python, Docker, Linux, TypeScript (company stack)

    TL;DR

    Owns complex data and evaluation programs for frontier AI labs and internal teams, from scoping through delivery, including managing external vendors. Works on quality procedures, delivery pipelines and logistics for LLM and agent evaluation data. Partners with research, platform and marketplace teams on product improvements.

    About HUD →

    The full posting

    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 a Delivery Engineer to own complex, time-sensitive data and evaluation programs for frontier AI labs, data vendors, and internal teams. You’ll turn ambiguous technical asks into executable programs, coordinate the people and dependencies required to deliver them, and ensure the resulting data is genuinely useful for evaluating and improving LLMs and agents. You’ll also manage vendors and build the processes, tooling, and operating rhythms that allow HUD to deliver reliably at increasing scale.

    Responsibilities

    • Own data and evaluation programs end-to-end, from initial scoping and requirements gathering through production, quality assurance, delivery, and retrospective
    • Translate ambiguous requests from AI labs and internal teams into clear specifications such as milestones, owners, dependencies, acceptance criteria, etc.
    • Maintain and improve data quality procedures using both quantitative signals and qualitative inspection, including analyzing task coverage, difficulty, reward distributions, etc.
    • Maintain and improve delivery pipelines at scale, which includes managing external vendors throughout the delivery lifecycle
    • Streamline the logistics behind data production and evaluation programs by improving workflows, documentation, automation, and cross-functional handoffs
    • Partner with research, platform, marketplace teams to translate learnings and feedback into product improvements

    Experience

    You may be a good fit if you have:

    • Experience owning complex technical programs in AI/ML, data operations, support engineering, applied research, forward-deployed engineering, or a similarly cross-functional environment
    • Strong quantitative and qualitative judgment about data—you can move between aggregate metrics and individual examples to determine whether a dataset or evaluation is useful, reliable, and representative
  • Experience maintaining and improving complex processes, especially within project delivery or data contexts
  • Demonstrated ability to bring structure to ambiguous problems, maintain momentum as requirements change, and make sound tradeoffs without waiting for a perfect specification
  • Strong written and verbal communication skills, including the ability to turn messy technical information into clear decisions, owners, and next steps
  • Strong candidates may also:

    • Experience with RLHF, reinforcement-learning environments, agent evaluations, human-in-the-loop data pipelines, annotation, or expert data collection
    • Experience supporting frontier AI labs, technical enterprise customers, or research teams with urgent and evolving requirements
    • Early-stage startup experience with ability to work independently in fast-paced environments

    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): $130,000 - $225,000
    • Singapore: $100,000 - $170,000
    • Rest of world: $100,000 - $170,000

    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!

    Compensation: $100K - $225K