Spring 2027 AI Applied Research Internship

Doist; Washington (District of Columbia); On-site; USD 28,000 - 40,000; Full time

Benefits offered by this job

Housing provided

Relocation support

Competitive compensation

Job summary

The Nuclear Company in Washington DC is seeking an AI/ML Intern to take models from data to production, deploying and owning the full lifecycle with full-time engineers on an NOS platform. The six-month co-op runs January–June 2027, with base location in DC and on-site five days weekly, including housing/relocation for those outside the DC area.

You will build ML pipelines, forecasting models, and monitor drift with tools like MLflow, Kubeflow, or SageMaker, delivering reliable, auditable

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.
• This position requires access to information and technology subject to U.S. export controls (including DOE 10 CFR Part 810 and NRC requirements). U.S. Person status (U.S. citizen or lawful permanent resident) is required, and visa sponsorship is not provided.
• Willing and able to work on-site in Washington DC, five days a week, for the full six-month term.

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 forecasting

Education

BS in Computer Science

MS in Computer Science

Tools

MLflow

Kubeflow

SageMaker

Job description

The Nuclear Company is the fastest growing AI tech-startup in the nuclear and energy space, pioneering a fleet-scale approach to building the next generation of nuclear reactors. Through our design-once, build-many model, we're accelerating the deployment of safe, reliable, and affordable nuclear energy. We operate with an AI-first mindset. Every employee is expected to leverage AI, technology, and the Nuclear Operating System (NOS) as integral components of their role to improve the quality, speed, and impact of their work. We expect every team member to continuously identify opportunities to automate workflows, enhance decision-making, improve processes, and contribute to the ongoing evolution of NOS as a strategic operating capability that enables The Nuclear Company to scale with excellence. We hire people who are driven by purpose, thrive in ambiguity, and are energized by building what has never been built before. Our team combines intellectual curiosity with high agency, embraces candid feedback and continuous learning, and holds themselves and others to exceptional standards. Our values— Trust, Responsibility, Unity, Scrappiness, and Tenacity —guide how we hire, collaborate, and make decisions every day. They are not words on a wall; they are the standard by which we operate. Trust is the foundation of our safety culture, fostering intellectual honesty, accountability, and open communication, while our values challenge every team member to execute with urgency, humility, resilience, and an unwavering commitment to our mission.

About the role

The United States is building nuclear power again, and The Nuclear Company is writing the software that makes it possible. NOS, the Nuclear Operating System, runs the regulatory, supply chain, cost, schedule, and field work behind real reactor construction. The work matters for national security, energy independence, andthe climate.

You will take models from raw data to production on problems that matter to a real build. As an AI/ML Intern, you work with data-scientist depth: build machine learning and forecasting models, deploy them, and own the full lifecycle, including pipelines, evaluation, and production monitoring for drift. You work next to full-time engineers and own a model end to end, from messy data to a running, monitored service that people rely on.

This is a six-month co-op available in Spring 2027 (January to June), aligned to the academic calendar. Base location is Washington DC, on-site five days a week, with full housing and relocation for co-ops outside the DC metro area.

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 withMLflow, 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 stayaccurateand audit-ready.

Required Experience

• 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 (coursework, research, projects, or an internship) building ML pipelines and evaluating models; comfortable approaching a time-series or forecasting problem from scratch.
• This position requires access to information and technology subject to U.S. export controls (including DOE 10 CFR Part 810 and NRC requirements). U.S. Person status (U.S. citizen or lawful permanent resident) isrequired, and TNC does not provide visa sponsorship for these roles.
• Willing and able to work on-site in Washington DC, five days a week, for the full six-month term.

Preferred Experience

• MLflow, Kubeflow, or SageMaker; drift detection and production monitoring.
• Strong statistics, probability, and experimental design; SQL and relational data modeling.
• Cloud data warehouses (Snowflake, Databricks,BigQuery); Palantir Foundry or AWS.
• Interest in energy, national security, industrial software, or regulated industries.
• Familiarity with nuclear engineering concepts (not required, we teach the domain)

Benefits

• Competitive compensation packages 401k with company match.
• Medical, dental, vision plans.
• Generous vacation policy, plus holidays.
• Estimated Starting Salary Range The estimated starting rate for this role is $25.00 an hour plus a $2,000 monthly housing stipend less applicable withholdings and deductions, paid on a bi-weekly basis. The actual pay offered may vary based on relevant factors as determined in the Company’s discretion, which may include experience, qualifications, tenure, skill set, availability of qualified candidates, geographic location, certifications held, and other criteria deemed pertinent to the particular role.

EEO Statement The Nuclear Company is an equal opportunity employer committed to fostering an environment of inclusion in the workplace. We provide equal employment opportunities to all qualified applicants and employees without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic. We prohibit discrimination in all aspects of employment, including hiring, promotion, demotion, transfer, compensation, and termination.

Export Control Certain positions at The Nuclear Company may involve access to information and technology subject to export controls under U.S. law. Compliance with these export controls may result in The Nuclear Company limiting its consideration of certain applicants.