Electrical Engineer with Python Proficiency - AI Trainer

Key Responsibilities

• Identify an appropriate electrical engineering simulation package and build problems whose solution genuinely hinges on that tool's core capabilities.
• Develop full Python solutions for each problem, providing all necessary netlist files and circuit definitions 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 adjust difficulty until the pass rate falls between 10% and 30%.
• Tune circuit topologies, operating conditions, and solver parameters iteratively, building an understanding of how the model navigates complex circuit, control, and power systems 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 Electrical 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.
• Able to work independently in a remote, fast-paced environment.

Nice-to-Have

• Working knowledge of one or more domain-specific electrical engineering tools, including but not limited to ngspice, scikit-rf, python-control, pandapower, or PyPSA, 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 circuit analysis, control systems, or power systems.
• Familiarity with containerized or sandboxed Linux execution environments.