AI Applied Research Internship - On-Site DC (Housing)

The Nuclear Company; Washington (District of Columbia); On-site; USD 74,000 - 78,000; Full time

Benefits offered by this job

Competitive compensation packages

401k with company match

Medical, dental, vision plans

Generous vacation policy

Job summary

The Nuclear Company in Washington, DC is seeking an AI/ML Intern for a six-month co‑op starting Spring 2027. You will take models from raw data to production, deploy ML pipelines, and own the full lifecycle with monitoring.

Based in DC, you will work on-site five days a week next to engineers, building impactful forecasts and models for megaprojects while gaining hands-on experience with MLflow, Kubeflow, and SageMaker.

Qualifications

• Currently enrolled in a BS or MS program in a technical field and available for a full six-month term.
• Strong Python skills and experience with the ML data stack (pandas, NumPy, scikit-learn).
• Experience building ML pipelines and evaluating models; able to tackle time-series/forecasting from scratch.

Responsibilities

• Take models from raw data to production: source, clean, explore, build, evaluate, and deploy.
• Build ML pipelines and manage experiments with MLflow, Kubeflow, or SageMaker.
• Develop 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 practices to ensure accuracy and audit readiness.

Skills

Python

ML data stack (pandas, NumPy, scikit‑L

Education

BS or MS in Computer Science / Data Science / Statistics / Applied Math

Tools

MLflow

Kubeflow

SageMaker

Job description

The Nuclear Company in Washington, DC is seeking an AI/ML Intern for a six-month co‑op starting Spring 2027. You will take models from raw data to production, deploy ML pipelines, and own the full lifecycle with monitoring.

Based in DC, you will work on-site five days a week next to engineers, building impactful forecasts and models for megaprojects while gaining hands-on experience with MLflow, Kubeflow, and SageMaker.