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Abundant

On-demand human operators ensure AI reliability

Research Intern Fellow

InternshipUpdated on 10/22/2026
$43.27/hr
San Francisco, CA, USA
In Person
AI & Machine LearningAI Research

About the job

Requirements
  • Research expertise in a related field such as computer science, machine learning, or natural language processing, ideally with work published at a major conference such as NeurIPS, ICML, or ICLR.
  • Ability to productize research, including high-stakes evaluation, large-scale benchmarking, and product feature development.
  • Proven experience shipping research directly to production and live systems, specifically in advanced post-training, distillation, and high-stakes evaluation methodologies.
  • Experience with large-scale agent systems, including orchestration frameworks, tool APIs, distributed execution, observability, and logging infrastructure.
  • A thoughtful, strategic perspective on the societal and safety impacts of deploying general-purpose AI systems.
  • Experience advising on or shaping governmental policy related to AI safety and governance, such as House of Lords or Online Safety Bill initiatives.
Responsibilities
  • Architect and execute a core research agenda to discover generalizable ideas that advance model reasoning and intelligence at scale, owning the research-to-production lifecycle and ensuring rapid deployment in live systems.
  • Partner with advanced AI research teams to design, engineer, and iterate on high-impact datasets and large-scale benchmarking efforts focused on alignment, safety, and optimal reward signals.
  • Autonomously identify, scope, and manage long-running research projects, selecting high-impact problems critical to scaling data for AGI and ASI.
  • Collaborate with engineering teams on data pipelines, internal tooling, and high-performance deep learning algorithm implementations.
  • Work with a mentor on a research proposal during the 12-week program and submit the resulting research to a major conference for review.
Desired Qualifications
  • Research work published at a major conference such as NeurIPS, ICML, or ICLR.

About the company

Abundant offers a human-in-the-loop platform that makes AI agents reliable in production by using an on-demand team of experts to intervene when AI encounters edge cases, especially in healthcare, legal, and finance. The AI handles routine tasks and, when stuck, calls the Human Intelligence API; a human completes the task and hands control back, with every interaction recorded to generate labeled data for continuous model improvement. Clients access a performance analytics dashboard to monitor these interventions. By combining dedicated human oversight with automatic data generation, Abundant aims to boost AI accuracy and task success for advanced AI labs, startups, and enterprises building multimodal agent-powered systems.

Company Size

11-50

Company Stage

Seed

Total Funding

$130K

Headquarters

San Francisco, California

Founded

2024

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Simplify's Take

What believers are saying

  • YC F24 and a 2024 launch keep Abundant early, focused, and fast-moving.
  • June 2025 docs claim 99.9% completion and under-one-minute response times.
  • Healthcare, legal, and insurance automation demand audit trails Abundant already emphasizes.

What critics are saying

  • Anthropic and OpenAI now ship native computer-use agents, compressing Abundant’s wedge.
  • Abundant’s documentation still says SDK is coming soon, exposing unfinished productization.
  • If enterprise buyers internalize human fallback, Abundant becomes replaceable labor, not software.

What makes Abundant unique

  • Abundant pairs AI agents with human experts, not generic support, for edge cases.
  • Docs in June 2025 still say SDK coming soon, signaling early product access.
  • Recorded interventions create proprietary training data and auditable trails for regulated workflows.

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Benefits

  • Health Insurance
  • Dental Insurance
  • Vision Insurance

Growth & Insights

Headcount

6 month growth

26%

1 year growth

26%

2 year growth

46%