Chemical Engineering Task Lead - AI Training & Evaluation
- Salary
- Not stated
- Level
- Lead
- Work type
- Remote · Pakistan only
- Visa
- Not stated
Open. First seen 15 October 2026.
The team: Talent Solutions
This role is one of 50 open in Talent Solutions. 41 were posted in the last 30 days.
WHAT THE TEAM WORKS WITH, ACROSS ITS POSTINGS
Python (16 of 50), C++ (15 of 50), JavaScript (9 of 50), Linux (9 of 50), C (8 of 50), MATLAB (8 of 50), TypeScript (8 of 50)
OTHER ROLES ON THIS TEAM
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From the team and dates on Gramian Consulting Group's own job board.
About the role
About Gramian
Gramian 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.
About the Role
We are seeking an experienced Chemical Engineering Expert to lead a team of technical trainers developing realistic, terminal-based engineering 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 that each task reflects authentic chemical engineering workflows. This role combines advanced chemical engineering knowledge, computational modeling, technical quality assurance, and team leadership to improve how AI systems solve complex engineering problems.
CONTRACT: Contractor assignment, 4 weeks
COMMITMENT: Hourly, up to 40h/week
LOCATIONS: Remote - Bangladesh, Brazil, Colombia, Egypt, Ghana, India, Pakistan, Indonesia, Kenya, Nigeria, Turkey, Vietnam
PROCESS: AI Interview
NOTES: PhD Degree is mandatory!
Key Responsibilities
- Lead, mentor, and coordinate a team of 5–10 technical trainers, ensuring consistent quality, productivity, and timely delivery.
- Review engineering tasks end to end, including problem statements, reaction kinetics, thermodynamic and property data, process flowsheets, computational environments, reference solutions, and automated tests.
- Validate tasks involving reaction engineering, thermodynamics, phase equilibria, transport phenomena, separation processes, process simulation, process control, optimization, combustion, and electrochemical engineering.
- Ensure tasks reflect realistic chemical engineering workflows and require meaningful, multi-step technical reasoning.
- Verify mass and energy balances, thermodynamic consistency, property data, unit handling, numerical accuracy, and solver convergence.
- Validate computational models, stiff ODE/DAE solvers, tolerances, initial conditions, dependencies, and simulation results for reproducibility.
- Review automated graders to ensure they assess meaningful engineering outputs, including conversion, yield, selectivity, purity, energy consumption, and process constraint satisfaction.
- Identify technical inaccuracies, unrealistic assumptions, incorrect tolerances, and opportunities to bypass genuine engineering calculations.
- Provide actionable technical feedback, track revisions, and ensure issues are resolved before task approval.
- Onboard trainers, allocate assignments, monitor quality and throughput, resolve technical blockers, and maintain documentation and best practices.
Requirements
- PhD, postdoctoral experience, or equivalent advanced technical expertise in Chemical Engineering.
- Strong programming skills in Python, Julia, C/C++, or MATLAB/Octave.
- Proficiency in Linux and command-line environments.
- Hands-on expertise in at least one major area, such as process modeling, reaction kinetics, thermodynamic modeling, process simulation, or optimization.
- Strong understanding of chemical engineering fundamentals, numerical methods, computational modeling, and technical validation.
- Experience reviewing complex technical work, chemical process simulations, computational models, or research outputs.
- Ability to evaluate mass and energy balances, thermodynamic assumptions, numerical accuracy, solver convergence, and computational reliability.
- Strong analytical judgment and the ability to identify technical errors, edge cases, and flawed engineering assumptions.
- Experience mentoring, reviewing, or leading small technical teams.
- Excellent written communication skills for precise technical feedback and documentation.
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