Electrical Engineer with Python Proficiency - AI Trainer

We're building a talent pool of Electrical Engineering professionals with Python proficiency to contribute to project-based AI development initiatives, focused on evaluating and enhancing frontier AI models.

Designed for electrical engineers 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 tools such as ngspice, scikit-rf, python-control, or pandapower, with verifiable, code-graded answers run inside isolated Linux environments.

Key Responsibilities

• Identify an appropriate electrical 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 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 adjusting 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.
• Ability 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.

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

We're building a talent pool of Electrical Engineering professionals with Python proficiency to contribute to project-based AI development initiatives, focused on evaluating and enhancing frontier AI models.

Designed for electrical engineers 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 tools such as ngspice, scikit-rf, python-control, or pandapower, with verifiable, code-graded answers run inside isolated Linux environments.

Key Responsibilities

• Identify an appropriate electrical 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 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 adjusting 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.
• Ability 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.

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