
2 - 10 employees
π€ Artificial Intelligence
π€ B2B
βοΈ SaaS
π₯ Funding within the last year
π° Seed Round on 2026-01
Artificial Intelligence β’ B2B β’ SaaS
Rise Data Labs is a company that builds high-fidelity training data, custom evaluations, domain-expert sourcing, and reinforcement-learning environments to help AI labs and enterprise teams train, evaluate, and oversee models. They provide US-based subject-matter experts (500k+), an automated talent engine for sourcing, vetting, matching and scheduling experts, and create model-ready outputs such as tasks, rubrics, verifiers, demonstrations, and feedback loops for SFT/RLHF and tool use scenarios. Their offerings focus on realistic, tool-enabled RL environments (APIs, developer tools, browser workflows) and human-in-the-loop evaluations to surface failure modes and improve model capabilities.
π₯ 7 minutes ago
Where this job comes from
Posted on Rise Data Labs's careers page, not through a job board
First seen by Remote Rocketship 7 minutes ago

2 - 10 employees
π€ Artificial Intelligence
π€ B2B
βοΈ SaaS
π₯ Funding within the last year
π° Seed Round on 2026-01
Artificial Intelligence β’ B2B β’ SaaS
Rise Data Labs is a company that builds high-fidelity training data, custom evaluations, domain-expert sourcing, and reinforcement-learning environments to help AI labs and enterprise teams train, evaluate, and oversee models. They provide US-based subject-matter experts (500k+), an automated talent engine for sourcing, vetting, matching and scheduling experts, and create model-ready outputs such as tasks, rubrics, verifiers, demonstrations, and feedback loops for SFT/RLHF and tool use scenarios. Their offerings focus on realistic, tool-enabled RL environments (APIs, developer tools, browser workflows) and human-in-the-loop evaluations to surface failure modes and improve model capabilities.
β’ Own projects end to end: scope, plan, execute, iterate, and deliver datasets for leading AI labs and enterprise customers. β’ Be the customer's main point of contact: run check-ins, share progress, manage expectations, and surface risks early. β’ Translate research needs into specs: write clear guidelines, rubrics, and task designs that shape how models are trained and evaluated. β’ Lead expert teams: recruit, onboard, and manage domain specialists (PhDs, engineers, clinicians, lawyers, analysts) to produce work at scale. β’ Own quality: design QA workflows, review samples, track metrics, and continuously raise the bar on data integrity. β’ Improve how we operate: build playbooks, tooling requests, and processes that make the next project faster and better.
β’ 2+ years of experience in project or program management, consulting, operations, or a similarly high-ownership role. β’ Exceptional written and verbal communication; comfortable working directly with technical customers. β’ Proven ability to turn ambiguous problems into structured, executable plans. β’ Strong attention to detail and a high bar for quality. β’ Comfort in fast-paced, startup environments with shifting priorities. β’ Bachelor's degree or equivalent practical experience. β’ Experience at an AI/ML company or with data annotation, RLHF, or model evaluation projects. β’ Background managing distributed or freelance teams. β’ Familiarity with LLMs and a genuine interest in how they are trained and evaluated.
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