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HUD

AI agent evaluation platform and benchmarks

Sales Development Representative

Sales Development RepresentativeConfirmed live in the last 24 hours
Full-timeRemote in Singapore

About the Job

Requirements

  • Clear spoken and written English, with confidence starting conversations by phone.
  • Persistence through unanswered calls and rejection while staying professional and respectful.
  • Reliable follow-through across many conversations, with organized notes and next steps.
  • Comfort using everyday sales tools, taking feedback, and improving your approach.

Responsibilities

  • Work through prospect lists, find the right contacts, and make cold calls and send relevant emails and LinkedIn messages every day.
  • Explain how listing on HUD works and why it may be valuable to the provider, answer common questions, and handle objections.
  • Follow up consistently and guide interested providers through sign-up and listing submission.
  • Collect the information needed for a complete listing and help providers when they get stuck.
  • Keep contact records and next steps current, and meet agreed daily outreach targets and weekly targets for complete listings that match buyer needs.

Desired Qualifications

  • Telesales, call-center, appointment-setting, customer support, or recruitment experience is useful.
  • AI, data, and coding experience are optional.

About the Company

HUD

AI agent evaluation platform and benchmarks

HUD provides an evaluation platform for AI agents that perform computer-use tasks. It offers an interface that connects to HUD evaluation environments, allowing users to run benchmarks across hundreds of environments and thousands of tasks. Users can integrate their agents using various adapters, and interact with the system through an asynchronous API for efficient experiments. The platform then collects telemetry and benchmarking results to inform agent improvements. HUD differentiates itself by concentrating on evaluating and improving knowledge-work agents across a wide range of tasks and environments, rather than just building models, and by enabling scalable, tool-enabled testing via adapters and an asynchronous workflow. The company’s goal is to help organizations and developers assess, compare, and enhance their AI agents so they perform better in real-world knowledge-work scenarios.

Company size
11-50
Company stage
Seed
Total funding
$130K
Headquarters
San Francisco, CA
Founded
2025

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