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Nuclearn builds AI software purpose-built for nuclear power operations, deployed across 60+ reactors globally. The stack—Python, PyTorch, Kubernetes, React, FastAPI, PostgreSQL—reflects a modern ML-first architecture, but the project list reveals the real complexity: on-premise deployments, legacy system integration, real-time monitoring for mission-critical safety workflows, and high-dimensional ML visualization. Engineering hiring is decelerating despite active work on CAP automation, SaaS provisioning, and domain-specific ML pipelines, suggesting the team is consolidating around core product stability rather than scaling new features.
Tech Stack 27 technologies
Core StackKubernetes React FastAPI Python JavaScript PostgreSQL Docker Podman Redis RabbitMQ Celery Sentry MongoDB TypeScript Redux Vite Webpack PyTorch Linux Netdata Microsoft 365 Teams OneNote Maximo Zustand React Query NVIDIA GPU
What Nuclearn Is Building
◆Challenges
- On-premise integration challenges
- Cloud environment configuration challenges
- System interoperability issues
- Reducing noise in error monitoring
- Data ingestion pipeline reliability
- Integration with legacy enterprise systems
- Real-time monitoring for nuclear operations
- High-dimensional ml visualization
- Scalable frontend architecture
- Keeping critical infrastructure reliable, efficient, and safe
▲Active Projects
- On-premise platform deployment
- Saas instance provisioning
- Devonway to cap ai connector
- Cap ai automation simulate-apply workflow
- Sentry error reduction for celery tasks
- Real-time monitoring interfaces for mission-critical nuclear operations
- High-dimensional ml visualization components for automated insights
- Robust frontend architecture and shared component system
- Customer-specific classification, extraction, and prediction tasks
- Custom ml pipelines for domain-specific problems
Hiring Activity
9 roles · 2 in 30d
Department
Seniority
Company intelligence
