Lead Scientific Engineer\\Programmer
Job in
Seattle, King County, Washington, 98127, USA
Listed on 2026-10-20
Listing for:
Accounting Search
Full Time
position Listed on 2026-10-20
Job specializations:
-
Software Development
Machine Learning/ ML Engineer, Data Scientist, AI Engineer (Applied/Software)
Job Description & How to Apply Below
Fast Growing Leader in dynamic simulation software for water resources, environmental systems and complex engineering problems.
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
- Partner with the founding engineer to formalize existing modeling, QA, and support methodology.
- Apply machine learning to accelerate, approximate, or extend traditional numerical simulation methods.
- Help identify opportunities to modernize existing algorithmic infrastructure.
- Mastersor 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
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