AI Research Internship: Build Production ML for Nuclear

The Nuclear Company; Washington; On-site; USD 52,000 - 76,000; Full time

Benefits offered by this job

Housing provided

Competitive compensation

401k

Medical/dental/vision

Generous vacation

Job summary

The Nuclear Company is seeking an AI/ML Intern to take models from raw data to production on problems that matter to a real build. You’ll deploy and own end-to-end ML workflows, alongside experienced engineers, with full lifecycle ownership including monitoring for drift.

The six-month co-op runs from January to June 2027, with base location in Washington DC, on-site five days a week and housing/relocation provided for out-of-area candidates.

Qualifications

• Currently enrolled in a BS or MS in Computer Science, Data Science, Statistics, Applied Math, or a related technical field. Available for a full six-month term and returning to school afterward.
• Strong Python and the ML data stack (pandas, NumPy, scikit-learn).
• Hands-on experience building ML pipelines and evaluating models; comfortable approaching a time-series or forecasting problem from scratch.

Responsibilities

• Take models from raw data to production: source, clean, and explore data, then build, evaluate, and deploy.
• Build ML pipelines and manage experiments and models with MLflow, Kubeflow, or SageMaker.
• Build forecasting and time-series models for megaproject cost, schedule, and risk.
• Own the full lifecycle and production monitoring, including drift detection and retraining triggers.
• Establish model evaluation and validation so results stay accurate and audit-ready.

Skills

Python

ML pipelines

Time-series

Pandas

NumPy

Scikit-learn

Education

BS/MS in Computer Science/Data Science

Tools

MLflow

Kubeflow

SageMaker

Job description

The Nuclear Company is seeking an AI/ML Intern to take models from raw data to production on problems that matter to a real build. You’ll deploy and own end-to-end ML workflows, alongside experienced engineers, with full lifecycle ownership including monitoring for drift.

The six-month co-op runs from January to June 2027, with base location in Washington DC, on-site five days a week and housing/relocation provided for out-of-area candidates.