HUD

Design and build interfaces across HUD’s platform and marketplace from early concepts through shipped product.Make agent runs, evaluation results, reward signals, and quality feedback understandable and actionable.Collaborate with research and engineering to turn complex reinforcement-learning and evaluation workflows into useful tools.Talk with users, observe their challenges, and

Build infrastructure for reliable environment execution, trajectory collection, and evaluation of agent behavior at scale.Develop reusable tools, APIs, and pipelines for launching experiments, managing datasets and configurations, and inspecting trajectories and evaluation results.Turn research prototypes and experimental workflows into tested, documented software that researchers c

Build systems that detect PII, quasi-identifiers, credentials, and other sensitive information and transform it according to data type and downstream use case.Develop and benchmark detection methods using rules, statistical models, classifiers, and LLM-based approaches.Build production pipelines that anonymize raw data before downstream processing, training, evaluation, or synthetic

Own production uptime, latency, provisioning speed, infrastructure cost, and incident response for core platform services.Build and maintain AWS infrastructure using Terraform, Kubernetes/EKS, Helm, Docker, EC2, CodeBuild, ECR, S3, IAM, networking, and secrets management.Design and improve scalable backend and platform systems, including capacity planning, autoscaling, queueing, bac

Lead detection and incident response from initial signal through alerting, containment, investigation, postmortem, and follow-up engineering work.Own the security roadmap across product security, cloud and infrastructure security, corporate security, incident response, and compliance.Secure HUD’s APIs, platform, and data systems through threat modeling, design and code reviews, auth

Develop product-facing tools for browsing environments, inspecting trajectories, reviewing task quality, debugging failures, and understanding model behavior.Build vendor-facing workflows for creating, submitting, testing, and iterating on RL environments and training data.Create dashboards and observability tools for environment quality, evaluation results, data collection progress