Senior Software Engineer, Reinforcement Learning
At a glance
Senior Machine Learning Engineering role at HUD. San Francisco · full-time · $100,000–$225,000 base.
aimlroles summary, based on the employer's posting.
What you'll do
- Build interfaces for exploring environments, reviewing trajectories and task quality, and investigating failures or model behavior
- Create partner workflows for submitting, testing, and refining RL environments and training data
- Develop dashboards that track environment quality, evaluation results, collection progress, grader problems, reward signals, and pipeline status
- Connect task creation, data collection, evaluation, quality checks, and RL training through backend services and APIs
- Turn unclear requests from research, operations, and go-to-market teams into systems that ship quickly
What you bring
- Strong software engineering skills, including Python and experience with a modern web stack such as React or TypeScript
- A track record of owning user-facing or internal products from start to finish
- Comfort working with cloud infrastructure, Docker, CI/CD, observability, and production debugging
Who this fits
This role suits a senior engineer with full-stack range who can build practical tools for both technical and non-technical users. The work involves close collaboration with research engineers, vendors, operations, and go-to-market teams. The role is full-time, with offices in San Francisco or Singapore; remote candidates need substantial overlap with either time zone. Relocation and visa support are available for strong full-time candidates moving to the US or Singapore.
From the employer
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 includes 4 International Olympiad medalists (IOI, ILO, IPhO), the former #1 ranked Catan player in the world, 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): $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 recruiting@hud.so or elsewhere if we missed your application!