[{"@context":"https://schema.org","@type":"JobPosting","title":"Member of Technical Staff, Safety","description":"

BOUT ABUNDANT

Abundant is a research lab focused on identifying approaches to solve the longest-horizon tasks.

We pride ourselves on having an extremely talent-dense team united behind our long-term approach to building businesses.

THE ROLE

As a Member of Technical Staff with a focus on Safety, you will work directly with Abundant's founding team to ensure that the research we are producing is conducted in a responsible manner and will benefit society as a whole. You will embed AI safety principles in to all of our company's workflows and products.

WHAT YOU’LL DO

Foundational Capability Research & Execution: Architect and execute research nested within Abundant's focus areas (long-horizon and simulation)
Drive the conversation: Establish Abundant as a leader in AI post-training safety.
Build novel tooling: Identify opportunities to build tooling that can help Abundant further our safety goals.

WHO YOU ARE

Exceptional Research Depth & Strategic Vision: A PhD in a related field (e.g., CS, ML, NLP) with a world-class publication record (NeurIPS, ICML, ICLR) is preferred. You must possess the velocity to master complex fields and a proven track record in the productization of research, encompassing high-stakes evaluation, large-scale benchmarking, and product feature development.ABOUT ABUNDANT
AI models rely on two fundamental ingredients: compute and data. Abundant is building the NVIDIA of training data. NVIDIA, the leader in compute, has a peak market cap of $5T and generated $130B in revenue last year as the need for scaling compute has exploded. We believe the need to scale data is just beginning, as we move beyond SFT and human supervision to RL and Learning from Experience.

Our founding team consists of former founders, ML engineers, roboticists and data leads from Waymo, Google, Mercor and AWS. Our team has previously worked with DeepMind to deploy deep learning models at 1B user scale, trained SOTA models for self-driving at Waymo, and scaled data pipelines of tens of thousands of human annotators at YouTube. Our pioneering work in human computation, synthetic data, simulation and RL give us the advantage in delivering results to our customers.

Why now? Training data is more important and more scarce than ever before. Scaling laws dictate that linear improvement in model performance demands an exponential increase in training data. But there is only one World Wide Web and most of it has already been trained on. The next advances will require major advances in simulation, synthetic data and learning from experience.

What happens if we succeed? Abundant will be the core enabler for not only AGI, but ASI and physical intelligence. Most of the challenges in model algorithms and compute are already solved. What’s missing? The data necessary to move from general knowledge to domain expertise; from chatbots to agents; and from text to multimodal and physical AI. Ask any AI researcher or robot","datePosted":"2026-09-16","employmentType":"FULL_TIME","hiringOrganization":{"@type":"Organization","name":"Abundant","sameAs":"https://abundant.com"},"url":"https://jobs.ashbyhq.com/abundant/4da99916-c29b-49a2-8e2d-1964b1838e11","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}}},{"@context":"https://schema.org","@type":"JobPosting","title":"Head of Recruiting","description":"
ABOUT ABUNDANT
AI models rely on two fundamental ingredients: compute and data. Abundant is building the NVIDIA of training data. NVIDIA, the leader in compute, has a peak market cap of $5T and generated $130B in revenue last year as the need for scaling compute has exploded. We believe the need to scale data is just beginning, as we move beyond SFT and human supervision to RL and Learning from Experience.

Our founding team consists of former founders, ML engineers, roboticists and data leads from Waymo, Google, Mercor and AWS. Our team has previously worked with DeepMind to deploy deep learning models at 1B user scale, trained SOTA models for self-driving at Waymo, and scaled data pipelines of tens of thousands of human annotators at YouTube. Our pioneering work in human computation, synthetic data, simulation and RL give us the advantage in delivering results to our customers.

Why now? Training data is more important and more scarce than ever before. Scaling laws dictate that linear improvement in model performance demands an exponential increase in training data. But there is only one World Wide Web and most of it has already been trained on. The next advances will require major advances in simulation, synthetic data and learning from experience.

What happens if we succeed? Abundant will be the core enabler for not only AGI, but ASI and physical intelligence. Most of the challenges in model algorithms and compute are already solved. What’s missing? The data necessary to move from general knowledge to domain expertise; from chatbots to agents; and from text to multimodal and physical AI. Ask any AI researcher or robot","datePosted":"2026-08-20","employmentType":"FULL_TIME","hiringOrganization":{"@type":"Organization","name":"Abundant","sameAs":"https://abundant.com"},"url":"https://jobs.ashbyhq.com/abundant/0357244d-80a6-4206-a4b9-c956e8ce3b56","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}}},{"@context":"https://schema.org","@type":"JobPosting","title":"Research Product Manager (RPM)","description":"
ABOUT ABUNDANT
As the need for scaling data becomes the core bottleneck to progress, moving from general knowledge to domain expertise, and from chatbots to agents. Abundant is solving this by designing and operating simulation infrastructure where next-generation models learn to reason and solve complex problems.

Our team is composed of high-impact former founders, ML engineers, roboticists, and data leads from companies like Waymo and Google, with experience deploying models at 1B user scale. We partner with a majority of the top AI labs, frontier startups, and F500 enterprises to enable AGI, ASI, and physical intelligence.
THE ROLE
Research PM (RPM) is a role unique to Abundant. RPMs are PMs of the model, unlike traditional PMs who own an application or a feature. RPMs design and implement model capabilities, either as part of an AI lab, data lab, or other research organization. This is a founding-level role with outsized ownership.
WHAT YOU’LL DO
- Co-design capabilities of the model: define areas of improvement for the model, along with the Researcher.
- Perform literature review: headroom analysis, identifying recent work in academic and industry circles.
- Run experiments and benchmarks: using our internal simulation stack and our open source tooling such as Oddish to define and hillclimb on the vertical.
- Become the voice of the model user: Talk to individual users and/or enterprises, in order to deeply understand where mod","datePosted":"2026-07-07","employmentType":"FULL_TIME","hiringOrganization":{"@type":"Organization","name":"Abundant","sameAs":"https://abundant.com"},"url":"https://jobs.ashbyhq.com/abundant/d497409d-f30a-4a34-88cd-ddbaf8d7a6eb","jobLocationType":"TELECOMMUTE","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":150000,"maxValue":210000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","title":"Member of Technical Staff, Research ","description":"
  ABOUT ABUNDANT
  AI models rely on two fundamental ingredients: compute and data. Abundant is building the NVIDIA of training data. NVIDIA, the leader in compute, has a peak market cap of $5T and generated $130B in revenue last year as the need for scaling compute has exploded. We believe the need to scale data is just beginning, as we move beyond SFT and human supervision to RL and Learning from Experience.
  
  Our founding team consists of former founders, ML engineers, roboticists and data leads from Waymo, Google, Mercor and AWS. Our team has previously worked with DeepMind to deploy deep learning models at 1B user scale, trained SOTA models for self-driving at Waymo, and scaled data pipelines of tens of thousands of human annotators at YouTube. Our pioneering work in human computation, synthetic data, simulation and RL give us the advantage in delivering results to our customers.
  
  Why now? Training data is more important and more scarce than ever before. Scaling laws dictate that linear improvement in model performance demands an exponential increase in training data. But there is only one World Wide Web and most of it has already been trained on. The next advances will require major advances in simulation, synthetic data and learning from experience.
  
  What happens if we succeed? Abundant will be the core enabler for not only AGI, but ASI and physical intelligence. Most of the challenges in model algorithms and compute are already solved. What’s missing? The data necessary to move from general knowledge to domain expertise; from chatbots to agents; and from text to multimodal and physical AI. Ask any AI researcher or robot","datePosted":"2026-07-07","employmentType":"FULL_TIME","hiringOrganization":{"@type":"Organization","name":"Abundant","sameAs":"https://abundant.com"},"url":"https://jobs.ashbyhq.com/abundant/bd12575c-2eaf-4e34-aa8a-df632bacc51b","jobLocationType":"TELECOMMUTE","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":200000,"maxValue":500000,"unitText":"YEAR"}}}]

BOUT ABUNDANT

THE ROLE

WHAT YOU’LL DO

WHO YOU ARE

ABOUT ABUNDANT

ABOUT ABUNDANT

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