Member of Technical Staff, Research (EU)
About the role
Role focused on leading research-to-production work at Abundant, architecting next-generation model reasoning and intelligence, with emphasis on data, alignment, and scalable systems.
Responsibilities
- Drive Foundational Research & Execution: Architect and execute a core research agenda to discover simple, generalizable ideas that advance model reasoning and intelligence at scale. This includes owning the full research-to-production lifecycle and ensuring rapid deployment of your work in live systems.
- Model Alignment & Data Strategy: Partner with the world's most advanced AI research teams to design, engineer, and iterate on high-impact datasets and large-scale benchmarking efforts that shape how frontier models behave, specifically focusing on critical alignment, safety, and defining optimal reward signals.
- Autonomous Problem Selection: Autonomously identify, scope, and manage long-running research projects, choosing the most impactful problems that are critical to scaling data for AGI/ASI.
- System Infrastructure: Collaborate closely with engineering teams on data pipelines, internal tooling, and high-performance deep learning algorithm implementations.
Qualifications
- A PhD in a related field (e.g., CS, ML, NLP) with a world-class publication record (NeurIPS, ICML, ICLR) is preferred.
- 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.
- Strategic & Ethical Leadership: Thoughtful, strategic perspective on societal and safety impacts of deploying general-purpose AI systems. Experience advising on or shaping governmental policy related to AI safety and governance is preferred.
Skills
Benefits
- Health, dental, vision + flexible PTO

About Abundant
Agent simulation and RL for researchers
Hello! 👋 We are a team of former ML engineers, founders, roboticists and ops leads who obsess about data and its impact on safe, reliable AI. We specialize in creating environments and datasets for RL by leveraging our experience in simulation and model training. By the numbers: • Powering 3 of the top 6 global AI labs and multiple Fortune 500 enterprises • Billions of training tokens generated each month, 2x month over month • Exclusive, global network of over 500 domain experts We believe humans are inherently creative, and thrive by pushing the frontier. We are working towards an abundant future--one where everyone has access to infinite intelligence, services and goods. Based in San Francisco, CA. We enjoy good food and good company. -- more info below -- Abundant is building the NVIDIA of training data. AI models rely on two fundamental ingredients: compute and 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 second-time founders, ML engineers and data leads from Waymo, Google, Meta and AWS. Our team has previously collaborated with DeepMind to classify hate speech in YouTube videos, trained SOTA models for self-driving, and scaled data pipelines with thousands of human annotators. Our pioneering work in human computation, synthetic data, imitation learning and RL give us a solid 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 new, diverse, and high-quality datasets, making training data more important and scarce than ever before. What happens if we succeed? Abundant will be the core enabler for AGI and beyond. Most of the challenges in model training are already solved. What’s missing is the data necessary to move from general knowledge to domain expertise; from chatbots to agents; and from digital intelligence to physical AI. Ask any AI researcher or roboticist: the core bottleneck to progress is the availability of data, i.e. “abundant data”. Abundant works with the most advanced AI labs and startups, as well as F500 enterprises.
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