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Forward Deployed Research Engineer

Updated

$100,000–$180,000Remote, hiring in California

Own end-to-end technical deployments for frontier AI labs, data vendors, and internal teams, diagnosing ambiguous problems and building rapid solutions across code, data, and environments.

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View posting at HUD

At a glance

Posted base pay

$100K–$180KBelow the median

The work

Builds what the customer runs

Balance

  1. Mostly building
  2. Mixed
  3. Mostly pre-sales or support

Project stages

  1. Pre-sales (not covered)
  2. Proof of concept (not covered)
  3. Implementation
  4. Operations
Coding
Writes production code
Builds for
Both
Level
Senior
Role
Technical lead

What they ask for

Tools

  • benchmarks
  • evaluation frameworks
  • reinforcement learning
  • AI data pipelines
  • Python

Visa

  • Sponsors visas

Less common in FDE jobs

  • Who you build for: Both8%
  • Sponsors visas26%
  • Fully remote26%

Share of US FDE postings that state each fact.

The job description from HUD

Posted by HUD on

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 an Applied Research Engineer to own implementation. Our data buyers and sellers often have time-sensitive asks such as troubleshooting and running evals or cleaning data at scale. You’ll take the lead on diagnosing ambiguous technical problems and resolving them. This work is broad and hands-on - the right fit is a strong generalist AI engineer who can move quickly and wants to work closely with frontier AI labs and data vendors.

Responsibilities

  • Own technical deployment requests from frontier AI labs, data vendors, and internal teams from triage to completion
  • Ask the right questions to clarify ambiguous asks and identify what actually needs to be done
  • Build tools and one-off pipelines to solve urgent customer or partner problems
  • Coordinate with research and GTM teams to unblock deployments
  • Balance speed and quality in situations where customers need fast turnaround and the path is not fully specified
  • Document recurring issues and turn repeated manual work into reusable tools or processes

Experience

You may be a good fit if you have

  • Core engineering experience, preferably in a forward deployed or customer success context
  • 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
  • Strong debugging instincts across code, data, and environments
  • Demonstrated ability to operate independently in ambiguous situations without a fully prescribed roadmap
  • Strong judgment about when to move fast, when to escalate, and when correctness or security requires extra care
  • Comfort working directly with technical customers, vendors, or cross-functional internal teams

Strong candidates may also have

  • Experience in applied research engineering or forward-deployed engineering
  • Experience handling urgent production, customer, or deployment issues
  • Early-stage startup experience with ability to work independently in fast-paced environments
  • Strong communication skills for remote collaboration across time zones

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 includes 4 International Olympiad medalists (IOI, ILO, IPhO), serial AI startup founders, and researchers with publications at ICLR, NeurIPS, etc.
  • 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
  • Other perks including an Equinox membership, 401k, 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): $105,000 - $180,000
  • Singapore: $100,000 - $135,000
  • Rest of world: $100,000 - $135,000

Due to high volume, we may not actively respond to every application, but feel free to contact us at recruiting@hud.so or elsewhere if we missed your application!

View posting at HUD

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Pay and conditions

Posted pay
$100,000–$180,000
Pay details

$100K – $180K

Location
San Francisco, CA
Work arrangement
Remote
Remote work restrictions
Remote candidates must work hours with 70–80% overlap with either San Francisco or Singapore time zones.
Employment type
Full-time
Visa sponsorship
Available