About the Role

Empower frontier research by building robust data systems and tooling that facilitate ambitious experimentation at Nucleus AI. As a Software Engineer for Research Data Infrastructure, you will develop and maintain the core data systems and tools researchers rely on for large-scale experiments, evaluations, and data pipelines. Your focus will be on providing reliable, flexible, and high-throughput infrastructure for managing datasets, experiment outputs, and measurement pipelines.

You will work closely with research teams, enabling them to prepare datasets, execute large jobs, analyze results, and iterate with confidence. This collaborative role is perfect for engineers who excel at translating research needs into durable and scalable engineering solutions.

Responsibilities:

• Build and maintain data infrastructure supporting large-scale research experiments, dataset generation, evaluations, and analysis workflows.
• Create tools and services for researchers to manage inputs, outputs, metadata, lineage, and reproducibility across experiments.
• Enhance the reliability and usability of pipelines for data preparation, experiment execution, and results aggregation.
• Design systems that enable rapid iteration while ensuring correctness, traceability, and operational visibility.
• Collaborate closely with researchers to understand evolving workflow needs and translate them into scalable platform capabilities.
• Support high-volume experimental workloads involving multimodal data, model outputs, and evaluation artifacts.
• Develop interfaces, automation, and internal tooling to reduce friction for research teams and shorten iteration cycles.

Qualifications:

• Strong software engineering experience in data systems, backend infrastructure, platform engineering, or research tooling.
• Experience with systems for experimentation, evaluations, large-scale pipelines, or internal data platforms.
• Comfortable working in environments with rapidly evolving requirements and close collaboration with technical users.
• Ability to write clear, maintainable code with a focus on reliability, observability, and developer ergonomics.
• Proficiency in Python and at least one additional language common in backend or infrastructure engineering.
• Passion for supporting researchers by building fast, robust, and thoughtfully designed tools.

What Makes Nucleus AI Different

At Nucleus AI, research and engineering are in constant dialogue. In this role, you will be instrumental in defining the infrastructure layer that transforms exploratory work into repeatable progress. The systems you build will directly influence how researchers test ideas, measure outcomes, and push the boundaries of our models and agents.

If you are motivated by building data infrastructure that amplifies research impact, we encourage you to apply.