Lead Scientific Engineer\\Programmer

The Recruiting Hive; Seattle (WA); On-site; USD 120,000 - 180,000; Full time

Job summary

The Recruiting Hive in Seattle is seeking a candidate to advance numerical methods and modeling capabilities within a state-of-the-art simulation framework. The role focuses on ownership of numerical algorithms, model building, verification, and documentation, with collaboration across engineering teams.

Experience applying AI/ML to scientific software and strong communication skills are valued as you help modernize our infrastructure and deliver reliable, impactful solutions.

Qualifications

• Masters or PhD in science or engineering with outstanding academic performance.
• Broad experience with applied math and numerical methods for solving science and engineering problems.
• Earth sciences or civil engineering background, preferably including contaminant transport modeling.
• Excellent written and verbal communication skills.

Responsibilities

• Own numerical and algorithmic development for simulation software.
• Contribute to model building, verification, and documentation.
• Collaborate with software engineers to integrate new numerical capabilities.
• Apply machine learning to accelerate or extend traditional methods.

Skills

C++ programming

Numerical methods

Communication skills

Team collaboration

Education

Masters or PhD in science or engineering

Tools

MATLAB

R

Tableau

Job description

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 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

• 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