The Nuclear Company
Summer 2027 AI/ML Engineering Intern
Washington, DC +1 · Internship · Posted Aug 7, 2026
- Location
- Washington, DC
Washington, District of Columbia, United States - Experience
- No years specified. The posting describes a six-month term, although it also identifies the internship as 12 weeks (May to August).
- Education
- Currently enrolled in a BS in Computer Science, Machine Learning, Data Science, Statistics, Mathematics, or a related technical field.
- Visa sponsorship
- U.S. Person status (U.S. citizen or lawful permanent resident) is required; TNC does not provide visa sponsorship for these roles.
About the job
Build and ship production AI/ML features, agents, data integrations, and model evaluation capabilities for the Nuclear Operating System used in reactor construction.
What you'll do
- Develop AI agents and workflows using NOS data, tools, MCP interfaces, and tool-use frameworks.
- Build data pipelines, integrations, predictive and anomaly-detection models, and contribute to the data ontology.
- Own model quality through evaluation criteria, acceptance thresholds, regression suites, monitoring, and issue triage.
What they ask for
- Currently enrolled in a relevant technical BS program; 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 through coursework or projects.
- Evidence of shipping working software or ML projects.
- U.S. Person status (U.S. citizen or lawful permanent resident); able to work on-site in Washington, DC, five days a week for the full term.
Nice to have
- Hands-on LLM and agent experience, such as RAG, evaluations, prompting, fine-tuning, or tool use.
- Experience with Palantir Foundry and AIP, AWS or another cloud platform; data analysis, MLOps, CI/CD, or relevant industry interests are also noted.
Pay
USD 25.00 an hour (starting rate; base pay); USD 2,000 monthly (housing stipend)
Tools
Python, PyTorch, Hugging Face, Palantir Foundry, AWS GovCloud, MCP, MLflow, SageMaker
AI focus
Build LLM-driven workflows, retrieval-augmented generation, agents, predictive and anomaly-detection models, and production evaluation and monitoring capabilities.
Model-written summary · the original posting is authoritative