Electrical Engineering

Job Description: Pod Lead – Electrical Engineering & Computer Science

Budget: $14 per hour

Experience: 3

Role Overview

We are seeking an experienced Electrical Engineering or Computer Science expert to lead a team of 5–10 technical trainers developing realistic, terminal-based scientific and engineering tasks for an AI training and evaluation initiative.

The role involves reviewing technical tasks for accuracy, reproducibility, and evaluation quality while mentoring trainers and maintaining consistent quality standards.

Key Responsibilities

• Lead and mentor a pod of 5–10 technical trainers, ensuring quality, productivity, and timely delivery.
• Review problem statements, codebases, circuit netlists, HDLs, datasets, computational environments, reference solutions, and automated tests.
• Validate tasks involving HPC, parallel computing, algorithms, distributed systems, compilers, operating systems, databases, ML systems, GPU computing, circuit design, signal processing, power systems, and embedded systems.
• Ensure tasks reflect realistic software engineering, research, and electrical engineering workflows.
• Verify algorithm complexity, numerical accuracy, memory management, concurrency, circuit laws, power balance, signal processing, timing constraints, and system stability.
• Validate compilers, simulation tools, dependencies, computational environments, and build processes.
• Identify unreliable tests caused by nondeterminism, race conditions, hardware-dependent thresholds, or simulation convergence issues.
• Review automated graders for functional correctness, performance, frequency response, waveforms, timing, efficiency, and system behavior.
• Identify technical inaccuracies, flawed assumptions, incorrect tolerances, and evaluation bypasses.
• Provide actionable feedback, track revisions, and ensure quality issues are resolved before task approval.
• Onboard trainers, allocate work, monitor quality and throughput, resolve blockers, and maintain technical documentation and best practices.

Required Qualifications

• Ph.D., postdoctoral experience, or equivalent advanced technical experience in Computer Science, Electrical Engineering, Computer Engineering, or a related discipline.
• Strong programming skills in C/C++, Rust, Python, Julia, Fortran, MATLAB/Octave, or hardware description languages (HDL).
• Advanced Linux and terminal proficiency.
• Hands-on expertise in at least one major area: parallel computing, systems programming, scientific software development, circuit simulation, signal processing, power systems, or digital hardware design.
• Strong understanding of algorithms, computational systems, numerical methods, software testing, or electrical engineering principles.
• Experience reviewing complex codebases, technical implementations, engineering simulations, or research outputs.
• Ability to evaluate algorithm correctness, computational performance, numerical accuracy, concurrency, and reliability.
• Strong analytical judgment to identify technical errors, edge cases, race conditions, and flawed engineering assumptions.
• Experience mentoring, reviewing, or leading small technical teams.
• Excellent written communication skills for technical feedback and quality documentation.

Nice to Have

• Experience with HPC and systems development tools such as MPI, OpenMP, CUDA, LLVM/GCC, CMake, gdb, Valgrind, perf, sanitizers, or Slurm.
• Familiarity with electrical engineering and hardware simulation tools such as ngspice, Xyce, Icarus Verilog, Verilator, GHDL, Yosys, pandapower, PyPSA, MATPOWER, openEMS, GNU Radio, or QEMU.
• Familiarity with Docker, Git, CI/CD pipelines, and automated testing frameworks such as pytest.
• Experience developing technical benchmarks, programming challenges, simulation-based evaluations, or automated grading systems.
• Experience developing or evaluating AI coding agents, terminal-based agents, or LLM-generated technical solutions.
• Open-source development or maintainer experience, particularly reviewing and validating external contributions.
• Industry experience in semiconductors, high-performance computing, power utilities, telecommunications, or embedded systems.
• Prior experience in AI training, technical quality control, benchmark development, or evaluation programs.