Pod lead - Electrical Engineering & Computer Science (Terminal Bench S

Zettamine Labs; United States; Remote; USD 96,000 - 179,000; Part time

Job summary

ZettaMine seeks a Pod Lead Electrical Engineering & Computer Science for Frontier AI Research. This remote, part-time role centers on designing and supervising terminal-based scientific and engineering tasks for a frontier AI training program.

Immediate start with 40 hours weekly and at least 8 overlap with PST. You will mentor a large team, review code, HDL, circuits, and datasets; ensure reproducible results, performance, and stability across HPC environments.

Qualifications

• PhD, postdoctoral experience, or equivalent advanced technical expertise in CS/EE/CE.
• Strong programming skills in C/C++, Rust, Python, Julia, Fortran, MATLAB/Octave, or HDL, with advanced Linux proficiency.
• Experience leading technical teams and mentoring; ability to review complex codebases and research outputs.
• Excellent written communication for technical feedback and documentation.

Responsibilities

• Lead and mentor a pod of approximately 510 technical trainers developing realistic, terminal-based scientific and engineering tasks for a frontier AI training and evaluation initiative.
• Review technical tasks end to end, including problem statements, codebases, circuit netlists, HDL, datasets, computational environments, reference solutions, and automated tests.
• Validate tasks involving HPC, parallel computing, algorithms, distributed systems, compilers, operating systems, databases, ML 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 accurately evaluate technical outputs such as functional correctness, performance, frequency response, waveforms, timing, efficiency, and system behavior.
• Identify technical inaccuracies, flawed assumptions, incorrect tolerances, and opportunities to bypass computation, simulations, or automated evaluations.
• Provide actionable technical feedback, track revisions, and ensure quality issues are resolved before task approval.
• Onboard trainers, allocate work, monitor quality and productivity, and resolve technical blockers.
• Maintain technical documentation, quality standards, and best practices throughout task development.

Skills

C/C++

Python

Linux

HDL

Parallel Computing

Software Testing

Technical Mentoring

Documentation

Education

PhD or postdoctoral experience in CS/EE/CE

Tools

HDL

Linux

Job description

Hello,

Greetings from ZettaMine!!!

Freelancing Opportunity :- We are hiring a Pod Lead Electrical Engineering & Computer Science (Terminal Bench Science) for a short-term Frontier AI Research, Scientific Computing &

Engineering Evaluation

project across the following location: India

Role: Pod Lead Electrical Engineering & Computer Science (Terminal Bench Science)

Educational Eligibility: PhD, postdoctoral experience, or equivalent advanced technical experience in Computer Science, Electrical Engineering, Computer Engineering, or a closely related discipline

Mode: Remote

Start: Immediate

Employment Type: Part-time

Availability

• Minimum 40 hours per week.
• Availability to work at least 8 hours per day.
• Minimum 4 hours of overlap with PST business hours.

Mandatory Eligibility Criteria

Technical Qualification:

• PhD, postdoctoral experience, or equivalent advanced technical expertise in Computer Science, Electrical Engineering, Computer Engineering, or a closely related field.
• Strong programming skills in C/C++, Rust, Python, Julia, Fortran, MATLAB/Octave, or Hardware Description Languages (HDL), with advanced Linux and terminal proficiency.
• Hands-on expertise in at least one major area: Parallel Computing | Systems Programming | Scientific Software Development | Circuit Simulation | Signal Processing | Power Systems | 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 the reliability of technical results.
• Strong analytical skills to identify technical errors, edge cases, race conditions, and flawed engineering assumptions.
• Experience mentoring technical teams, reviewing deliverables, and maintaining quality standards.
• Excellent written communication skills for providing precise technical feedback and documenting engineering requirements.

What Youll Work On

• Lead and mentor a pod of approximately 510 technical trainers developing realistic, terminal-based scientific and engineering tasks for a frontier AI training and evaluation initiative.
• 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, ML 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 accurately evaluate technical outputs such as functional correctness, performance, frequency response, waveforms, timing, efficiency, and system behavior.
• Identify technical inaccuracies, flawed assumptions, incorrect tolerances, and opportunities to bypass computation, simulations, or automated evaluations.
• Provide actionable technical feedback, track revisions, and ensure quality issues are resolved before task approval.
• Onboard trainers, allocate work, monitor quality and productivity, and resolve technical blockers.
• Maintain technical documentation, quality standards, and best practices throughout task development.

Thanks & Regards,

Sowmya P

ZettaMine