This position will have a direct impact in developing new modeling capabilities to enhance our state-of-the-art modeling and simulation framework. Job Scope: Numerical & Algorithmic Ownership Model Building & Verification . Documentation & Knowledge Transfer Collaboration & Support • Work alongside the software engineering team to integrate new or improved numerical capabilities into the br • Partner with the founding engineer to formalize existing modeling, QA, and support methodology. Growth & Modernization • Apply machine learning to accelerate, approximate, or extend traditional numerical simulation methods. • Help identify opportunities to modernize existing algorithmic infrastructure. Requirements • Masters or PhD level in science or engineering, with outstanding academic performance. • Broad experience with applied math and numerical methods for solving science and engineering problems (e.g., matrix algebra, numerical methods for solving partial differential equations). • Earth sciences or civil engineering background, preferably including contaminant transport modeling. • Extensive C++ programming experience, ideally in scientific or engineering applications; familiarity with commercial or open-source numerical libraries and frameworks is a plus. • Proven ability to design and implement practical numerical solutions to real-world problems. • Good communications skills, must write effectively and enjoy interacting with other team members. • Experience developing and supporting Windows desktop applications is a plus, as is hands-on experience with data science tools such as MATLAB, R, or Tableau. Experience applying AI/ML techniques (e.g., machine learning models, LLM-based tools, or AI-assisted development) to scientific or engineering software is