{"id":2619606,"url":"https://alion.io/job/gramian-consulting-group-electrical-engineering-computer-science-task-lead-ai-projects","title":"Electrical Engineering & Computer Science Task Lead (AI Projects)","company":{"id":5702,"name":"Gramian Consulting Group","domain":"gramianconsultinggroup.com","url":"https://alion.io/company/gramianconsultinggroup","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":"contractor","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":["ID","KE","NG","PK","TR","VN"],"hiring_countries_total":6,"salary":null,"salary_estimate":{"min_usd":75000,"max_usd":180000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":1119},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C++","optional":false},{"name":"Fortran","optional":false},{"name":"HPC","optional":false},{"name":"Julia","optional":false},{"name":"Linux","optional":false},{"name":"Machine Learning","optional":false},{"name":"MATLAB","optional":false},{"name":"Python","optional":false},{"name":"Rust","optional":false}],"status":"live","first_seen_at":"2026-10-15T12:59:47Z","employer_posted_date":"2026-10-15","last_verified_at":"2026-10-18T23:00:10Z","board_verified":true,"closed_at":null,"days_open":3,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":3},"description":"About Gramian\nGramian 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.\nAbout the Role\nWe 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.\nCAPACITY: Minimum 40 hours per week, at least 4 hours per day\nSENIORITY: Senior / Technical Lead\nLANGUAGE: Strong written English\nKey Responsibilities\nLead and mentor a team of 5-10 technical trainers, ensuring consistent quality, productivity, and timely task delivery.\n\nReview technical tasks end to end, including problem statements, codebases, circuit netlists, hardware description languages (HDL), datasets, computational environments, reference solutions, and automated tests.\n\nValidate 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.\n\nEnsure tasks reflect realistic software engineering, research, and electrical engineering workflows requiring meaningful, multi-step technical reasoning.\n\nVerify technical correctness across algorithm complexity, numerical accuracy, memory management, concurrency, circuit laws, power balance, signal processing, timing constraints, and system stability.\n\nValidate compilers, simulation tools, software dependencies, computational environments, and build processes to ensure reproducible results.\n\nIdentify unreliable tests caused by nondeterministic behavior, race conditions, hardware-dependent performance thresholds, or simulation convergence issues.\n\nReview automated graders to ensure they assess meaningful technical outputs, including functional correctness, performance, frequency response, waveforms, timing, efficiency, and system behavior.\n\nIdentify technical inaccuracies, flawed assumptions, incorrect tolerances, and ways tasks could be bypassed without genuine computation or engineering analysis.\n\nProvide actionable 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