Lead Scientific Engineer\\Programmer

Gallin Associates

Washington (District of Columbia)

On-site

USD 110,000 - 160,000

Full time

7 days ago
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Job summary

Gallin Associates seeks a skilled specialist to advance numerical modeling and simulation capabilities within our cutting-edge water resources and environmental systems framework. You will own numerical algorithms, build models, verify results, and document methodologies while collaborating with software engineers to integrate improvements.

The role emphasizes strong C++ programming, experience with numerical libraries, and the application of AI/ML to scientific software.

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 (e.g., matrix algebra, numerical methods for solving PDEs).
  • Earth sciences or civil engineering background, preferably including contaminant transport modeling.
  • Extensive C++ programming experience in scientific or engineering applications; familiarity with numerical libraries and frameworks.
  • 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; experience with MATLAB, R, or Tableau is a plus.
  • Experience applying AI/ML techniques to scientific or engineering software is a plus.

Responsibilities

  • Ownership of numerical and algorithmic development.
  • Model building and verification of modeling framework.
  • Documentation and knowledge transfer across the team.
  • Collaboration and support with software engineering.
  • Work alongside the founding engineer to formalize modeling, QA, and support methodologies.
  • Growth initiatives: apply ML to accelerate or extend simulations; modernize algorithmic infrastructure.

Skills

C++ programming
Numerical methods
Machine learning
Communication skills
Software design
Windows apps

Education

Master's or PhD in Science/Engineering
Earth sciences background
Civil engineering background

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 brPartner 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
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