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HUD

Senior Software Engineer, Reinforcement Learning

San Francisco; Singapore; Remote (Asia); Remote (North America)Remote · APAC
Senior · FullTime · Engineering & Research
POSTED 21 AUGVERIFIED 1H AGO
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Pay · posted
$100k–225k
mkt median $207k
Open for
74d
since 21 Aug
Hiring · 30d
37
0 net · open roles
TypeScriptJavaScriptReactNext.jsPythonAWSKubernetesDockerTerraform

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 Senior Software Engineer, Reinforcement Learning to build the product surfaces, backend systems, and internal tools that power HUD’s RL data engine.

You’ll own product surfaces end-to-end, including backend services, APIs, databases, dashboards, tools, vendor workflows, data collection, and observability for RL rollouts. You don’t need to be a researcher, but you need to work research engineers and vendors to translate ambiguous needs into polished products that enable our RL systems.

Responsibilities

Develop product-facing tools for browsing environments, inspecting trajectories, reviewing task quality, debugging failures, and understanding model behavior

Build vendor-facing workflows that make it easy for external partners to create, submit, test, and iterate on RL environments and training data

Create dashboards and observability tools that surface environment quality, eval results, data collection progress, grader issues, reward signal problems, and pipeline health

Design backend services and APIs that connect task authoring, data collection, evaluation, QA/QC, and RL training infrastructure

Partner closely with research, operations, and GTM teams to turn vague, high-stakes requests into well-designed systems that ship quickly

Experience

You may be a good fit if you have

Strong software engineering fundamentals and real full-stack range, including proficiency in Python and a modern web stack such as React, TypeScript, Next.js, or similar

Experience owning user-facing or internal products end-to-end

Good product taste and the ability to build tools that are intuitive for both technical and non-technical users

Comfort with cloud infrastructure, Docker, CI/CD, observability, and production debugging

High agency—you identify what needs to exist, build it, and improve it without waiting for a perfect spec

Strong communication skills for working across research, engineering, operations, vendors, and founders

Strong candidates may also have

Experience building data collection, labeling, annotation, eval, or research tooling platforms

Experience building dashboards, review workflows, observability tools, or debugging interfaces for complex systems

Experience building developer tools, infrastructure products, internal platforms, or workflow products that made a team dramatically faster

Experience with AWS, Kubernetes, Terraform, Docker, Grafana, or similar infrastructure tools as tools to ship product, not as the center of the role

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.

Source · HUDFirst seen 2 NovOriginal ↗