About Abundant

Agent simulation and RL for researchers

Tech description:

Job 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 roboticist: the core bottleneck to progress is the availability of data, hence “_abundant data_”. Abundant works with a majority of the top AI labs, as well as frontier startups and F500 enterprises. ## About the Role As Researcher, you will work on moving the field of agentic capabilities forward by delivering results to our customers and/or publishing to top-tier venues such as NeurIPS, ICLR, ICML. As part of this role, you will lead end to end experiments in reinforcement learning, data, simulation, and agentic capabilities. ### Requirements Deep experience in one or more of the following: * ML engineering or research * Reinforcement learning * Research in agentic harnesses or harness optimization * Agent evaluation and benchmarking * Simulation in the robotics or agent setting * CI/CD tooling, OS/kernel development, Docker We’re looking for folks that are _obsessive_ about their work. In data, quantity is important but data _quality_ is the differentiator for the winner in the space. In addition to this mindset, here are some skills that are a pre-requisite for working in startups: * Extremely clear communication. We value being able to explain very complex technical concepts in very simple terms. * Pragmaticsm. Able to go deep, but also to simplify and prioritize. * Velocity. Fast at getting work done and picking up new skills. * Curious about AI and technology; keeping up with the latest papers in agents, RL and benchmarks. * Impact-oriented. Hacker. Always works on the most important 20% of the project in successive chunks. * Handle extremely ambiguity. Able to unblock yourself and others. _Here are three different personas that will succeed at Abundant:_ **The Craftsman** The Craftsman cares about their work, simply for the art of it. They may put extra care into UX or design, or into data quality, or customer success. The Craftsman is energized by putting out great work. **The Underdog** The Underdog is dying to prove themselves. They’ve overlooked; they haven’t challenged by their school or company, or they are tired of politics at a FAANG company. They’re looking for a chance to maximize their full potential and talent. **The Antifragilist** Our team collectively has an uncommon trait: high pain tolerance. The Antifragilist is not simply stoic in the face of challenge. They are like an immune system: they grow and become stronger in the face of each challenge. # Why Join Abundant? 1. You’ll get to work on the core of AI (models and data), serving top researchers in the field. 2. You’ll get to work with experienced operators who care deeply about building a team and having a long-lasting impact. 3. You will future-proof your career, as all work moves from the first-order (doing the work) to second-order (automating the work). ## Why _not_ join Abundant? Here’s what you’re signing up for when you interview with us. 1. We have high appetite for risk and ambition. A lot of work will feel like experimental research, because it is! 2. We enjoy working with other folks who hold themselves to the highest standard, and expecting our teammates to hold us to the same bar. 3. The simulation/RL industry is new, fast-paced and dynamic. We value first-principles thinking over prior experience. You may not end up using any of the skillsets you come in with.

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