Civil Engineer with Python Proficiency - AI Trainer

Kake; Austin (TX); On-site; USD 70,000 - 90,000; Full time

Job summary

Kake is seeking a Civil Engineering professional proficient in Python to contribute to AI development initiatives. This role involves simulating complex engineering problems using tools like OpenSeesPy and CalculiX.

The candidate should have a background in Civil Engineering with a minimum of 2 years of relevant experience. You will be responsible for developing Python solutions and analyzing AI model outputs, ensuring a good understanding of the engineering context.

Remote work in a fast-paced environment is expected, coupled with excellent communication skills.

Qualifications

• Minimum 2 years of hands-on experience in engineering research or applied work.
• Strong ability to write and validate computational solutions in Python.
• Capable of developing problems that require specialized simulation tools.

Responsibilities

• Select and design civil engineering problems using simulation software.
• Develop Python solutions with necessary input and geometry definitions.
• Analyze results from AI models and adjust parameters accordingly.
• Collaborate with senior reviewers and refine tasks as needed.

Skills

Python proficiency

Engineering research

Excellent communication skills

Simulation software expertise

Education

Academic background in Civil Engineering

Tools

OpenSeesPy

CalculiX

YADE

bempp-cl

Job description

We're building a talent pool of Civil Engineering professionals with Python proficiency to contribute to project-based AI development initiatives, focused on evaluating and enhancing frontier AI models. Designed for civil engineering professionals who enjoy deep technical problem-solving, this pipeline role is for those looking to apply their simulation expertise to evaluate and push the boundaries of frontier AI models, relying on domain-specific simulation tools, such as OpenSeesPy, CalculiX, YADE, or bempp-cl, with verifiable, code‑graded answers run inside isolated Linux environments.

Key Responsibilities

• Identify an appropriate civil engineering simulation package and build problems whose solution genuinely hinges on that tool's core capabilities, whether solvers, simulation kernels, or domain‑specific models
• Develop full Python solutions for each problem, providing all necessary input files, geometry definitions, and boundary conditions as required
• Establish the correct numerical output and define how close the AI model needs to get, using tolerance values appropriate to the engineering context
• Run the problem against the AI model across multiple parallel attempts, analyzing where it succeeds or falls short, and adjusting difficulty until the pass rate falls between 10% and 30%
• Tune load cases, boundary conditions, and solver parameters iteratively, building an understanding of how the model navigates complex structural and geotechnical problems
• Hand off completed tasks to a senior reviewer in your subfield and refine based on their feedback before final submission

Core Requirements

• Academic background in Civil Engineering or a closely related field
• At least 2 years of hands‑on experience in engineering research, applied work, or teaching
• Solid Python skills, applied to writing and validating computational solutions
• Capacity to build problems that cannot be solved without specialized simulation software
• Excellent written and verbal communication skills in English
• Ability to work independently in a remote, fast‑paced environment

Nice‑to‑Have

• Working knowledge of one or more domain‑specific civil engineering tools, including but not limited to OpenSeesPy, CalculiX, YADE, or bempp-cl, or a demonstrated ability to get up to speed independently
• Prior exposure to how frontier AI models approach complex simulation tasks
• Knowledge spanning more than one engineering domain, such as structural analysis, geotechnical modeling, or boundary element methods
• Familiarity with containerized or sandboxed Linux execution environments

Please note: Due to the high volume of applications, only shortlisted candidates will be contacted.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.