Electrical Engineering Lead – AI Projects

Job not on LinkedIn

🔥 12 hours ago

🌐 Turkey, Nigeria, +4 more countries – Remote

🇹🇷 Turkey – Remote 🇳🇬 Nigeria – Remote 🇰🇪 Kenya – Remote 🇵🇰 Pakistan – Remote 🇮🇩 Indonesia – Remote 🇻🇳 Vietnam – Remote

⏳ Contract/Temporary

🟠 Senior

🔋 Electrical Engineer

👻 Ghost score 12%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Gramian Consulting

WebsiteLinkedInAll Job Openings

2 - 10 employees

Founded 2025

💼 Consulting

📦 Logistics

📣 Marketing

Consulting • Logistics • Marketing

Gramian Consulting is a remote-first consulting firm that connects engineering and data/AI talent with organizations through talent augmentation, recruiting, dedicated teams, and contractor management. The firm provides Data & AI services including LLM training and fine-tuning, AI agents and assistants, MLOps, and AI infrastructure, and it offers mentorship and education programs for career readiness, interview preparation, and international market orientation. Rooted in hands-on engineering and recruiting experience, Gramian helps clients scale technical teams and extract business value from AI while developing individual talent.

📋 Description

• 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

• 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.