Apply for the 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.

Apply for the 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, 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.