Electrical Engineering & Computer Science Task Lead (AI Projects)

About Gramian Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs. About the Role We are seeking an experienced Computer Science, Electrical Engineering, or Computer Engineering Expert to lead a team of technical trainers developing realistic, terminal-based tasks for advanced AI training and evaluation. You will oversee a pod of approximately 5–10 trainers, review tasks for technical accuracy, reproducibility, and grading reliability, and ensure they reflect authentic software, computational, and electrical engineering workflows. This role combines advanced technical expertise, computational problem-solving, quality assurance, and team leadership to help evaluate and improve next-generation AI systems. CONTRACT: Contractor assignment, 4 weeks COMMITMENT: Hourly, up to 40h/week LOCATIONS: Remote - Bangladesh, Brazil, Colombia, Egypt, Ghana, India, Pakistan, Indonesia, Kenya, Nigeria, Turkey, Vietnam PROCESS: AI Interview NOTES: PhD Degree is mandatory! Key Responsibilities Lead and mentor a team of 5–10 technical trainers, ensuring consistent quality, productivity, and timely task delivery. Review technical tasks end to end, including problem statements, codebases, circuit netlists, hardware description languages (HDL), datasets, computational environments, reference solutions, and automated tests. Validate tasks involving high-performance computing (HPC), parallel computing, algorithms, distributed systems, compilers, operating systems, databases, machine learning systems, GPU computing, circuit design, signal processing, power systems, and embedded systems. Ensure tasks reflect realistic software engineering, research, and electrical engineering workflows requiring meaningful, multi-step technical reasoning. Verify technical correctness across algorithm complexity, numerical accuracy, memory management, concurrency, circuit laws, power balance, signal processing, timing constraints, and system stability. Validate compilers, simulation tools, software dependencies, computational environments, and build processes to ensure reproducible results. Identify unreliable tests caused by nondeterministic behavior, race conditions, hardware-dependent performance thresholds, or simulation convergence issues. Review automated graders to ensure they assess meaningful technical outputs, including functional correctness, performance, frequency response, waveforms, timing, efficiency, and system behavior. Identify technical inaccuracies, flawed assumptions, incorrect tolerances, and ways tasks could be bypassed without genuine computation or engineering analysis. Provide actionable technical feedback, track revisions, and ensure quality issues are resolved before task approval.