Summer 2027 AI/ML Engineering Intern

The Nuclear Company•Washington, DC

21h•Onsite

About The Position

The Nuclear Company is seeking an AI/ML Engineering Intern for Summer 2027 to work on the Nuclear Operating System (NOS). This role involves building AI and machine learning capabilities within NOS, focusing on LLM-driven workflows, retrieval-augmented generation, and agents that interact with NOS data and tools. The intern will work alongside full-time engineers and domain experts, contributing to production models and features that are used in the construction of nuclear power plants. The internship is a 12-week program from May to August, based in Washington DC, requiring on-site work five days a week. Housing and relocation assistance are provided for those outside the DC metro area.

Requirements

Currently enrolled in a BS in Computer Science, Machine Learning, Data Science, Statistics, Mathematics, or a related technical field.
Available for a full six-month term and returning to school afterward.
Strong Python fundamentals and hands-on exposure to modern ML and LLM tooling (PyTorch, Hugging Face, or similar) through coursework or projects.
A track record of shipping working software or ML projects (course projects, personal projects, or prior internships or co-ops).
U.S. Person status (U.S. citizen or lawful permanent resident) is required due to U.S. export controls.
Willing and able to work on-site in Washington DC, five days a week, for the full six-month term.

Nice To Haves

Hands-on experience with LLMs and agents: prompting, fine-tuning, retrieval-augmented generation, evals, or tool use (MCP or similar frameworks).
Coursework or project experience with Palantir Foundry and AIP, AWS, or another major cloud platform — Foundry exposure is heavily weighted.
Solid data fundamentals: comfortable doing exploratory data analysis and working with large, messy datasets, including time-series or sensor data.
Exposure to MLOps tooling (MLflow, SageMaker, Vertex AI) or CI/CD for models.
Interest in energy, national security, industrial software, or regulated industries.
Familiarity with nuclear engineering concepts.

Responsibilities

Ship ML and AI features inside NOS applications used by teams for site evaluation, red flag analysis, scheduling, lessons learned, and stakeholder/project tools.
Build AI agents and agent workflows that operate against NOS data and tools, including MCP interfaces and tool-use frameworks.
Develop data pipelines and integrations across Palantir Foundry, AWS GovCloud, and other platforms, contributing to the data ontology for reliable model and agent use.
Build predictive and anomaly-detection models for operations and engineering decisions, including time-series analysis of sensor and operational data.
Own model quality end-to-end, including eval criteria, acceptance thresholds, and regression suites to ensure NOS is audit-ready and results are reproducible; triage issues and root-cause failures.