Aalo Atomics is looking to revolutionize energy for a sustainable future by making nuclear energy globally accessible, starting with the Aalo-1, a 10 MWe reactor, and the job is to design and deploy ML systems that accelerate nuclear regulatory workstreams and augment reactor engineering and operations
Requirements
- Strong programming in Python and modern ML frameworks (PyTorch, TensorFlow, etc.)
- Demonstrated experience fine‑tuning and evaluating foundation models (prompting, adapters/LoRA, distillation, safety/robustness evals)
- Proven ability to build end‑to‑end ML applications: data pipelines, retrieval/grounding, inference services, and monitoring
- Experience with Microsoft Azure
- Familiarity with safety‑critical software practices: version control, testing, reproducible ML workflows, change control
- Background in numerical methods, scientific computing, or physics‑based modeling
- Experience with optimization methods (Bayesian optimization, evolutionary algorithms, reinforcement learning) for complex engineering systems
Responsibilities
- Design and implement large language model-driven solutions for nuclear regulatory, engineering, and operational contexts, within an agentic framework
- Develop RAG and tool‑use flows over internal and public corpora (e.g., regulatory guidance, procedures, technical reports) to ground outputs and reduce hallucinations
- Build evaluation harnesses and guardrails for reliability, transparency, and traceability of model outputs
- Create pipelines that automate regulatory documentation generation, review, and compliance mapping
- Apply reinforcement learning, simulation, and optimization (e.g., Bayesian methods, evolutionary algorithms) to improve design and operational parameters
- Establish scalable infrastructure for training, testing, and deployment (containerized services, experiment tracking, CI for ML, dataset/version governance)
- Design for secure, possibly air‑gapped and on‑prem environments; integrate with monitoring/observability for models in production
Other
- Work with engineering, regulatory affairs, product, and operations to align ML capabilities with nuclear and data‑center applications
- Collaborate with nuclear engineers to translate physics and safety models into ML‑driven decision‑support tools and human‑in‑the‑loop workflows
- Comfortable working fully on‑site in Austin and collaborating closely with domain experts across disciplines
- Primarily office/lab work on‑site in Austin; occasional hands‑on work with compute and test equipment; ability to use a computer for extended periods
- Ability to work in a team environment and collaborate with cross-functional teams
