Electrical Engineering & Computer Science Task Lead (AI Projects)

• Lead and guide a team of 5 to 10 technical trainers to ensure high-quality, timely task completion.
• Review all aspects of technical tasks, including problem statements, code, circuit designs, datasets, and automated tests for accuracy and reproducibility.
• Validate tasks related to high-performance and parallel computing, algorithms, distributed systems, compilers, operating systems, databases, machine learning, GPU computing, circuit and signal processing, power systems, and embedded systems.
• Ensure tasks represent realistic workflows requiring complex technical reasoning in software and electrical engineering.
• Check technical correctness in areas such as algorithm complexity, numerical precision, memory and concurrency management, circuit laws, power balance, timing, and system stability.
• Verify compilers, simulation tools, software dependencies, and build processes to guarantee consistent results.
• Identify unreliable tests caused by nondeterministic effects, race conditions, hardware-specific limits, or simulation convergence problems.
• Review automated grading systems to confirm they accurately assess functional correctness, performance, timing, efficiency, and system responses.
• Detect technical mistakes, incorrect assumptions, improper tolerances, and potential task bypasses that avoid genuine engineering analysis.
• Provide clear technical feedback, track task revisions, and ensure quality standards before approval.
• Manage trainer onboarding, work allocation, quality control, issue resolution, and maintain technical documentation and best practices.

• Hold a PhD, postdoctoral experience, or equivalent advanced expertise in Computer Science, Electrical Engineering, Computer Engineering, or a closely related field.
• Have strong programming skills in languages such as C/C++, Rust, Python, Julia, Fortran, MATLAB/Octave, or hardware description languages (HDL).
• Be highly proficient with Linux and command-line interfaces.
• Possess practical experience in at least one key area like parallel computing, systems programming, scientific software, circuit simulation, signal processing, power systems, or digital hardware design.
• Demonstrate a solid grasp of algorithms, computational systems, numerical methods, software testing, and electrical engineering concepts.
• Have experience analyzing complex codebases, technical implementations, engineering simulations, or research results.
• Be able to assess algorithm correctness, computational efficiency, numerical accuracy, concurrency, and technical dependability.
• Show strong analytical skills to identify errors, edge cases, race conditions, and faulty engineering assumptions.
• Have experience mentoring or leading small technical teams.
• Exhibit excellent written communication skills for detailed technical feedback and documentation.

Apply through the employer's official contact by submitting your application before the closing date. The employer has not published a closing date.