
Voice data for AI
Besimple AI is building the data and benchmark infrastructure for the next generation of voice AI. We help AI understand people across languages, accents, and real-world conversations. Our founders are former Meta product and engineering leaders from MIT and Brown, and we work directly with frontier AI labs.
We’re building a crowdsourcing platform where people contribute to paid projects that help improve AI. We’re looking for someone to grow its social presence, manage its online community, and find creative ways to recruit new contributors.
You should enjoy making content, starting conversations, and getting people involved. Maybe you’ve grown your own social account, recruited members for a campus organization, built an online community, or found an unexpected way to get people excited about something. We care about what you’ve done and how you think, whether that experience comes from a job or something you built yourself.
In this role, you will:
We’re especially interested in three things:
You should also write clearly, use good judgment in public conversations, and follow through consistently. You’re comfortable with spreadsheets and basic analytics, and willing to learn tools that make monitoring, publishing, and reporting easier.
Success means our channels are active and responsive, contributors know where to find opportunities and get help, and we can see which activities bring qualified people onto the platform. You’ll help us build a reliable system for learning what works and doing more of it.
When applying, please share:
At Besimple AI, we’re making it radically easier for teams to build and ship reliable AI by fixing the hardest part of the stack: data. Good evaluation, training and safety data require domain experts, robust tooling and meticulous QA. AI teams and labs come to us to get high quality data so they can launch AI safely. We’re a YC X25 company based in Redwood City, CA, already powering evaluation and training pipelines for leading AI companies across customer support, search, and education. Join now to be close to real customer impact, not just demos.
High-quality, human-reviewed data is still the single biggest driver of model quality, but most teams are stuck with old tools and legacy processes that do not scale to modern, multimodal, agentic workflows. Besimple replaces that mess with instant custom UIs, tailored rubrics, and an end-to-end human-in-the-loop workflow that supports text, chat, audio, video, LLM traces, and more. We meet teams where they are—whether they need on-prem deployments and granular user management or a fast cloud setup—to turn evaluation into a continuous capability rather than a one-time project.
Founders previously built the annotation platform that supported Meta’s Llama models. We’ve seen how world-class annotation systems shape model quality and iteration speed; we’re bringing those lessons to every AI team that needs to ship with confidence. You’ll work directly with the founders and users, owning problems end-to-end—from an interface that unlocks a tough rubric, to a workflow that reduces disagreement, to a AI judge system that improves quality.
If you’re excited by systems that combine product design, human judgment, and applied AI—and you want to build the data and evaluation layer that keeps AI trustworthy—come build with us. See how fast teams can go from raw logs to a robust, human-in-the-loop eval pipeline—and how that changes the way they ship AI.