{"id":3266752,"url":"https://alion.io/job/weekday-technical-lead-electrical-engineering-and-computer-science","title":"Technical Lead Electrical Engineering and Computer Science","company":{"id":7097,"name":"Weekday","domain":"weekday.works","url":"https://alion.io/company/weekday","size_band":"51-200","is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"B","score":81,"open_postings":90,"ghost_share":0,"stale_share":0.978,"repost_share":0,"time_to_fill_p50_days":6,"computed_at":"2026-10-27T05:46:45Z"}},"role":"Industrial Engineering","role_family":"Industrial Engineering","seniority":"lead","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["IN"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":20000,"max_usd":48000,"period":"year","method":"role_seniority_country_cell","sample_n":15},"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":"C","optional":true},{"name":"CI/CD","optional":true},{"name":"CMake","optional":true},{"name":"CUDA","optional":true},{"name":"Docker","optional":true},{"name":"GHDL","optional":true},{"name":"Git","optional":true},{"name":"Icarus Verilog","optional":true},{"name":"LLVM","optional":true},{"name":"MPI","optional":true},{"name":"Ngspice","optional":true},{"name":"OpenMP","optional":true},{"name":"Pytest","optional":true},{"name":"QEMU","optional":true},{"name":"SLURM","optional":true},{"name":"Valgrind","optional":true},{"name":"Verilator","optional":true},{"name":"Xyce","optional":true},{"name":"Yosys","optional":true}],"status":"live","first_seen_at":"2026-10-26T09:36:16Z","employer_posted_date":"2026-10-26","last_verified_at":"2026-10-27T13:32:54Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"This role is for one of Weekday’s clients\nMin Experience: 7+ years\nLocation: Remote (India)\nJobType: full-time\nWe are seeking an experienced Technical Lead with a strong background in Electrical Engineering, Computer Science, or Computer Engineering to lead a team of technical trainers responsible for developing realistic, terminal-based scientific and engineering tasks for AI training and evaluation.\nIn this role, you will lead a team of approximately 5-10 technical trainers, oversee end-to-end task development and validation, and ensure that every task meets high standards of technical accuracy, reproducibility, and evaluation quality. You will work across software systems, scientific computing, and electrical engineering domains, ensuring that tasks reflect authentic engineering workflows and require meaningful, multi-step technical reasoning.\nRequirements\nKey Responsibilities\nTeam Leadership and Mentorship: Lead, mentor, and onboard a team of technical trainers. Allocate assignments, monitor productivity and quality, resolve blockers, and ensure timely delivery of high-quality technical tasks.\n Technical Review and Validation: Review tasks end to end, including problem statements, codebases, circuit netlists, hardware description languages (HDLs), datasets, computational environments, reference solutions, and automated tests.\n Scientific and Engineering Task Development: Validate tasks across 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.\nTechnical Accuracy: Verify algorithmic correctness, computational complexity, numerical precision, memory management, concurrency behavior, circuit laws, power balance, signal processing accuracy, timing constraints, and system stability.\nEnvironment and Reproducibility: Validate compilers, simulation tools, software dependencies, build processes, and computational environments to ensure consistent and reproducible results.\nTesting and Evaluation Quality: Review automated tests and graders to ensure they assess meaningful technical outcomes, including functional correctness, performance, frequency response, waveforms, timing, efficiency, and overall system behavior.\nReliability and Edge-Case Analysis: Identify nondeterministic tests, race conditions, hardware-dependent performance thresholds, simulation convergence issues, incorrect tolerances, flawed assumptions, and potential ways to bypass computational or simulation requirements.\nQuality Assurance: Provide precise, actionable feedback, track revisions, and ensure identified issues are resolved before tasks receive final approval.\nTechnical Documentation: Establish and maintain technical guidelines, review standards, documentation, and best practices to ensure consistency across the team.\nContinuous Improvement: Improve task development and evaluation processes, strengthen technical quality standards, and contribute to the development of reliable benchmarks for AI training and assessment.\nMust-Have Skills\nStrong expertise in Electrical Engineering and Computer Science, with the ability to evaluate complex technical implementations across relevant engineering domains.\nProficiency in C/C++, along with experience in programming languages such as Python, Rust, Julia, Fortran, MATLAB/Octave, or hardware description languages.\nAdvanced proficiency in Linux environments, command-line tools, and terminal-based development workflows.\nHands-on expertise in at least one major technical domain, such as parallel computing, systems programming, scientific software development, circuit simulation, signal processing, power systems, or digital hardware design.\nStrong understanding of algorithms, computational systems, numerical methods, software testing, or electrical engineering fundamentals.\nExperience reviewing complex codebases, engineering simulations, technical implementations, or research outputs.\nAbility to evaluate computational performance, algorithmic correctness, numerical accuracy, concurrency, and system reliability.\nStrong analytical and problem-solving skills, with the ability to identify technical errors, edge cases, race conditions, and flawed engineering assumptions.\nExperience leading, mentoring, or reviewing the work of small technical teams.\nExcellent written communication skills and the ability to provide clear technical feedback and maintain quality documentation.\nGood-to-Have Skills\nExperience with parallel and high-performance computing technologies such as MPI, OpenMP, and CUDA.\nFamiliarity with systems development tools such as LLVM/GCC, CMake, GDB, Valgrind, performance profilers, sanitizers, and Slurm.\nExperience with electrical engineering and hardware simulation tools such as ngspice, Xyce, Icarus Verilog, Verilator, GHDL, Yosys, pandapower, PyPSA, MATPOWER, openEMS, GNU Radio, or QEMU.\nFamiliarity with Docker, Git, CI/CD pipelines, and automated testing frameworks such as pytest.\nExperience developing technical benchmarks, programming challenges, simulation-based evaluations, or automated grading systems.\nExposure to AI coding agents, terminal-based agents, large language models, or AI-generated technical solutions.\nOpen-source development or maintainer experience, particularly reviewing and validating external contributions.\nIndustry experience in semiconductors, high-performance computing, power utilities, telecommunications, or embedded systems.\nPrevious experience in AI training, technical quality assurance, benchmark development, or evaluation programs.\nEducation and Experience\nPh.D., postdoctoral research experience, or equivalent advanced technical expertise in Computer Science, Electrical Engineering, Computer Engineering, or a closely related discipline.\nDemonstrated experience leading technical teams and 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