SWE Intern

Abundant • San Francisco, CA

3d

About The Position

Abundant is building the NVIDIA of training data. 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. 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. 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.

As a Software Engineering Intern (Research Focused), you will work closely with our engineering team and founders to support the development of customer-facing products and internal research tooling. This role is designated as a general research internship, focusing exclusively on research, evaluation, and benchmark design. You will assist in tasks related to the Core Platform , including core simulation engines, data creation tooling, and experimentation platforms. Your primary focus will be on benchmarking and evaluation tasks to help the team maintain high data quality standards. In this role, you will spend the majority of your time coding and executing experiments under the guidance of a mentor. You will contribute to improving simulation performance and help transition core features into more modular components while learning how to handle large-scale event processing.

Requirements

• Students or recent graduates with experience or strong interest in one or more of the following: Large language model (LLM) research and effectiveness studies, Evaluation and benchmark design for AI agents, Proficiency with AI coding agents and development tools, Foundational knowledge in Python, data science, or machine learning.
• Obsessive about their work.
• Extremely clear communication. Able to explain very complex technical concepts in very simple terms.
• Pragmatism. 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.
• Ability to navigate experimental ambiguity and create novel approaches.
• High pain tolerance.
• First-principles thinking over prior experience.

Nice To Haves

• 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 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 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.

Responsibilities

• Support the development of customer-facing products and internal research tooling.
• Focus exclusively on research, evaluation, and benchmark design.
• Assist in tasks related to the Core Platform, including core simulation engines, data creation tooling, and experimentation platforms.
• Focus on benchmarking and evaluation tasks to help the team maintain high data quality standards.
• Spend the majority of your time coding and executing experiments under the guidance of a mentor.
• Contribute to improving simulation performance.
• Help transition core features into more modular components.
• Learn how to handle large-scale event processing.

Benefits

• Work on the core of AI (models and data), serving top researchers in the field.
• Work with experienced operators who care deeply about building a team and having a long-lasting impact.
• Future-proof your career, as all work moves from the first-order (doing the work) to second-order (automating the work).

What This Job Offers

• Job Type: Full-time
• Career Level: Intern
• Education Level: No Education Listed