Research Engineer, Synthetic Data

hud (YC W25)

. Build HUD’s synthetic data pipeline for RL training data and evals for frontier AI agents .

Posted 9/23/2026full-timeSan Francisco • California • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Proficient in building synthetic data pipelines and analyzing model performance, with a strong understanding of synthetic data quality and its limitations. Capable of designing diverse and realistic synthetic tasks while collaborating effectively in remote environments.

Highest-signal resume keywords

Proficiency In PythonExperience With Synthetic Data Research MethodsBuilding Synthetic Data Pipelines End-To-EndStrong Communication SkillsDetail-Oriented

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonSynthetic Data Research MethodsData Pipeline DevelopmentTask DesignPerformance AnalysisMetrics Development

Soft Skills

Detail-OrientedStrong Communication SkillsIndependent Work

Tools & Technologies

DockerLinux

Industry Keywords

Synthetic DataReinforcement LearningTask Learning OutcomesEvaluation BenchmarksEarly-Stage Startup Experience

Tech Stack

Tools & technologies

DockerLinuxPython

About the role

Key responsibilities & impact

Build HUD’s synthetic data pipeline for RL training data and evals for frontier AI agents
Work with subject-matter experts to create synthetic tasks across professional and technical domains
Design methods that generate diverse, realistic, and learnable synthetic tasks
Build systems and tooling to mutate, validate, and improve synthetic tasks
Analyze model and agent performance to understand task learning outcomes and failure modes
Develop metrics for synthetic task diversity, realism, and learnability
Complete a process involving two technical interviews and a 2–3 day work trial

Requirements

What you’ll need

Proficiency in Python, Docker, and Linux environments
Experience with synthetic data research methods; applicants should elaborate in their application
Strong understanding of what “good synthetic data” means and its limitations
Experience building synthetic data pipelines end-to-end without a fully prescribed roadmap
Experience working on environments, evals, and benchmarks
Detail-oriented and able to spot subtle inconsistencies or edge cases in synthetic data
Able to reason from first principles about task design, scoring, and failure modes
Early-stage startup experience and ability to work independently in fast-paced environments
Strong communication skills for remote collaboration across time zones
Motivated candidates are encouraged to apply even if they do not meet all criteria

Benefits

Comp & perks

100% covered top-of-the-line medical, dental, and vision from Blue Shield of CA (US employees)
Lunch and dinner when you’re in the office (in-office employees)
Company-wide holiday break from Christmas Eve to New Year’s Day on top of PTO and paid holidays
Equinox membership (US employees)
401k (US employees)
Commuter benefits (US employees)
Unlimited access to tokens for ChatGPT, Claude Code, Cursor, etc.
Support for relocation and visas for strong full-time candidates to the US or Singapore