AI/ML Engineer

The Nuclear Company•Washington, DC

6d•$121,000 - $165,000

About The Position

The Nuclear Company is hiring an AI Engineer to ship the machine learning and agent capabilities inside NOS, the software platform behind one of the largest nuclear buildouts in the United States. You’ll work in the Platform Integration & AI/Data squad and report to the Director of Platform Integrations. This is a hands-on engineering role. You’ll embed ML models and LLM-driven workflows directly into the NOS applications our internal teams and partners use every day: site evaluation, red flag analysis, scheduling, lessons learned, and the stakeholder and project tools that run across active TNC projects. You’ll work close to the metal: training and fine-tuning models, designing agent workflows against NOS data and tools, wiring up MCP interfaces, and standing up the evals and monitoring that keep AI features safe in production. You’ll partner daily with platform engineers, product engineers, and the nuclear domain experts who use what you ship. The team is small, the pace is fast, and the work is visible, what you build will be demoed to utilities, regulators, and financial partners making 20-to-30-year decisions about the future of American nuclear power.

Requirements

Bachelor’s or Master’s in Computer Science, Machine Learning, Statistics, or a related technical field, or equivalent production experience.
5+ years of professional experience shipping ML or AI features into production. We care about what you’ve shipped, not just what you’ve studied.
Strong Python and hands-on experience with modern ML and LLM tooling (PyTorch, Hugging Face, or similar).
Production experience with LLMs and agents: prompting, fine-tuning, RAG, evals, tool use.
Solid data engineering fundamentals, comfortable building data pipelines and working with large, messy datasets.
Experience with at least one major cloud, AWS preferred.
Strong written and verbal communication. You can explain models, tradeoffs, and failure modes to non-specialists.

Nice To Haves

Experience with Palantir Foundry and AIP. Given the central role Foundry plays in our platform, this is heavily weighted.
Experience building agent systems with MCP or similar tool-use frameworks.
MLOps experience (MLflow, SageMaker, Vertex AI) and CI/CD for models.
Experience in a regulated or safety-critical industry: nuclear, aerospace, defense, energy, or medical.
Background in time-series, sensor, or operational data.
Comfortable doing exploratory data analysis and translating findings into product decisions, in addition to shipping production models.

Responsibilities

Ship ML and AI features inside NOS. Train, fine-tune, and deploy models and LLM-based workflows into production, with the evals, monitoring, and safety controls that make them trustworthy.
Build AI agents and agent workflows. Design agents that operate against NOS data and tools, including the MCP interfaces and tool-use frameworks they depend on.
Own model quality end-to-end. Define eval criteria, acceptance thresholds, and regression suites for AI features. Keep results reproducible and the bar high.
Partner across the squad. Work directly with platform engineers and product engineers so models reach production instead of staying in notebooks.
Contribute to the data ontology. Help shape how NOS data is structured so models and agents can use it reliably.
Build predictive and anomaly-detection models that support operations and engineering decisions, including time-series analysis of sensor and operational data from active projects.