Chemical Engineering Task Lead - AI Training & Evaluation

Gramian Consultancy is a boutique firm specializing in IT professional services and engineering talent solutions. We leverage deep expertise in software engineering and leadership to help organizations build high-performing teams by connecting them with professionals who align closely with their technical and cultural needs. Currently, we are looking for an experienced Chemical Engineering Expert to lead a team of technical trainers focused on developing realistic, terminal-based engineering tasks for advanced AI training and evaluation. This role involves managing a pod of 5 to 10 trainers, ensuring the technical accuracy and reproducibility of tasks, and maintaining grading reliability. The ideal candidate will combine advanced chemical engineering knowledge with computational modeling skills and team leadership to enhance how AI systems address complex engineering challenges. This is a full-time position requiring a minimum commitment of 40 hours per week, with at least 4 hours worked daily. Strong written English communication is essential.

Key Responsibilities

- Lead, mentor, and coordinate a team of 5 to 10 technical trainers, ensuring consistent quality, productivity, and timely delivery of tasks.
- Review engineering tasks comprehensively, including problem statements, reaction kinetics, thermodynamic and property data, process flowsheets, computational environments, reference solutions, and automated tests.
- Validate tasks related to reaction engineering, thermodynamics, phase equilibria, transport phenomena, separation processes, process simulation, process control, optimization, combustion, and electrochemical engineering.
- Ensure that tasks accurately reflect real-world chemical engineering workflows and require meaningful, multi-step technical reasoning.
- Verify mass and energy balances, thermodynamic consistency, property data accuracy, unit handling, numerical precision, and solver convergence.
- Validate computational models, including stiff ODE/DAE solvers, tolerances, initial conditions, dependencies, and simulation reproducibility.
- Review automated graders to confirm they assess meaningful engineering outputs such as conversion, yield, selectivity, purity, energy consumption, and process constraint satisfaction.
- Identify technical inaccuracies, unrealistic assumptions, incorrect tolerances, and potential shortcuts that bypass genuine engineering calculations.
- Provide actionable technical feedback, track revisions, and ensure all issues are resolved before task approval.
- Onboard new trainers, allocate assignments, monitor quality and throughput, resolve technical blockers, and maintain comprehensive documentation and best practices.

Required Qualifications

- 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 chemical engineering area such as process modeling, reaction kinetics, thermodynamic modeling, process simulation, or optimization.
- Deep understanding of chemical engineering fundamentals, numerical methods, computational modeling, and technical validation.
- Experience reviewing complex technical work, including chemical process simulations, computational models, or research outputs.
- Ability to critically evaluate mass and energy balances, thermodynamic assumptions, numerical accuracy, solver convergence, and computational reliability.
- Strong analytical judgment with the ability to detect technical errors, edge cases, and flawed engineering assumptions.
- Experience mentoring, reviewing, or leading small technical teams.
- Excellent written communication skills for delivering precise technical feedback and maintaining documentation.

This role offers the opportunity to lead a specialized team at the intersection of chemical engineering and AI, driving innovation in how complex engineering problems are solved through computational methods. Candidates should be prepared for a senior or technical lead position requiring strong leadership and technical expertise.