Electrical Engineering & Computer Science Lead – AI Projects

Gramian Consulting

. Lead and mentor a team of 5–10 technical trainers, ensuring consistent quality, productivity, and timely task delivery.

Posted 10/16/2026contractRemote • Bangladesh, Brazil, Colombia, Egypt, Ghana, IndiaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates advanced technical expertise in Computer Science or Electrical Engineering, with strong programming skills in multiple languages and hands-on experience in high-performance computing and systems programming. Capable of leading and mentoring technical teams while ensuring quality and accuracy in complex engineering tasks.

Highest-signal resume keywords

PhD Or Postdoctoral ExperienceProgramming Skills In C/C++, Rust, Python, Julia, Fortran, MATLAB/OctaveAdvanced Proficiency In Linux And Command-Line EnvironmentsExperience In Parallel Computing And Systems ProgrammingStrong Analytical Judgment

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

High-Performance ComputingParallel ComputingAlgorithmsCircuit DesignSignal ProcessingEmbedded SystemsSoftware TestingNumerical MethodsTechnical ReviewTechnical Feedback

Soft Skills

MentoringWritten CommunicationAnalytical Judgment

Tools & Technologies

CompilersSimulation ToolsAutomated GradersComputational EnvironmentsBuild Processes

Industry Keywords

Electrical EngineeringComputer ScienceComputer EngineeringTechnical DocumentationEngineering Simulations

Tech Stack

Tools & technologies

Distributed SystemsLinuxPythonRustC++

About the role

Key responsibilities & impact

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.
Onboard trainers, allocate work, monitor quality and throughput, resolve technical blockers, and maintain technical documentation and best practices.

Requirements

What you’ll need

PhD, postdoctoral experience, or equivalent advanced technical expertise in Computer Science, Electrical Engineering, Computer Engineering, or a closely related discipline.
Strong programming skills in C/C++, Rust, Python, Julia, Fortran, MATLAB/Octave, or hardware description languages (HDL).
Advanced proficiency in Linux and command-line environments.
Hands-on expertise in at least one major area, such as 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 behavior, and technical reliability.
Strong analytical judgment and the ability 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 precise technical feedback and documentation.