Lead Scientific Engineer\\Programmer

Job Juncture; Seattle (WA); On-site; USD 120,000 - 190,000; Full time

Job summary

Job Juncture in Seattle seeks a highly skilled numerical methods and algorithms specialist to advance our modeling framework for water resources and environmental systems.

This role emphasizes ML application, C++ development, and collaboration with engineering teams to deliver robust scientific software. A strong academic record and good communication are essential.

Qualifications

• Masters or PhD in science or engineering with outstanding academic performance.
• Strong background in applied math and numerical methods for solving science and engineering problems.
• Earth sciences or civil engineering background, preferably including contaminant transport modeling.
• Extensive C++ programming experience in scientific or engineering applications.
• Experience with data science tools like MATLAB, R, or Tableau.
• Good writing and communication skills; enjoy interacting with team members.

Responsibilities

• Own numerical and algorithmic development for the modeling framework.
• Collaborate with software engineering to integrate new capabilities.
• Apply machine learning to accelerate or extend numerical methods.
• Support QA and knowledge transfer within the team.

Skills

C++ programming

Numerical methods

Applied math

Communication skills

Data science tools knowledge

Education

Masters or PhD in science or engineering

Tools

MATLAB

R

Tableau

Numerical libraries

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

Documentation & Knowledge Transfer

• 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