Research Fellow
$168k - $168k • Remote • San Francisco • FullTime
Posted 1mo ago
Job Location
San Francisco
Tech Stack
Remote Work Policy
Fully remote
Employment Type
FullTime
Categories
AI Research Engineer
About the job
Abundant is building the NVIDIA of training data, recognizing the critical need for scaling data as AI models advance beyond supervised learning to reinforcement learning and learning from experience. Our founding team brings deep expertise from leading AI organizations, with a proven track record in deploying large-scale deep learning models, training state-of-the-art self-driving models, and managing massive data pipelines. We are at the forefront of innovation, addressing the scarcity of training data by advancing simulation, synthetic data generation, and learning from experience, which are essential for achieving AGI, ASI, and physical intelligence. We partner with top AI labs and enterprises to provide the data necessary for models to move from general knowledge to domain expertise and from chatbots to agents.
Responsibilities
- Architect and execute a core research agenda to advance model reasoning and intelligence at scale, managing the full research-to-production lifecycle.
- Design, engineer, and iterate on high-impact datasets and large-scale benchmarking efforts in collaboration with advanced AI research teams, focusing on model alignment and safety.
- Autonomously identify, scope, and manage long-running research projects critical to scaling data for AGI/ASI.
- Collaborate with engineering teams on data pipelines, internal tooling, and high-performance deep learning algorithm implementations.
Requirements
- Research expertise in a related field (e.g., CS, ML, NLP), ideally with publications at major conferences (NeurIPS, ICML, ICLR).
- Proven ability to master complex fields and productize research, including high-stakes evaluation, large-scale benchmarking, and product feature development.
- Experience shipping research directly to production and live systems, focusing on 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.
- Thoughtful, strategic perspective on the societal and safety impacts of general-purpose AI systems.
- Experience advising on or shaping governmental policy related to AI safety and governance.
Benefits
- Health, dental, vision
- Flexible PTO