AI Design Engineer

Job Description Summary The AI Design Engineer will lead the technical development and deployment of advanced AI, machine learning, and GenAI solutions across the nuclear and energy domains. This role requires deep expertise in model development, pre-training, and implementation of AI algorithms—including vision AI, predictive analytics, LLM-based applications, and anomaly detection. The engineer will work closely with domain experts to translate operational challenges into AI-solvable problems, prototype models, validate performance, and support integration with enterprise systems. Strong Python and data science skills, familiarity with cloud AI platforms, and experience with MLOps pipelines are essential. This role is critical to delivering high-impact technical solutions across diverse business use cases such as factory vision systems, error analysis, and procedural automation. Job Description Responsibilities: In this role, you will: Develop custom tools and utilities to enhance the generative AI pipeline. These tools may include data preprocessing scripts, model evaluation dashboards, and content visualization interfaces. Streamline repetitive tasks by automating processes, improving efficiency, and reducing manual intervention. Collaborate with QA engineers to design comprehensive test suites for the generative AI models. Write unit tests to validate individual components, ensuring robustness and reliability. Work closely with data scientists to create diverse and effective prompts for the generative models. Participate in prompt fine-tuning experiments to improve model performance. Integrate generative AI models into existing applications and services via APIs. Ensure seamless deployment across various platforms, including cloud environments. Cross-Functional Communication: Collaborate with data engineers, DevOps, and product teams to align project goals. Maintain clear and concise documentation for tools, APIs, and integration procedures Required Qualificati...