Materials Science AI Model Evaluation Expert

About OpenTrain
OpenTrain is the centralized, open platform where AI training and data-labeling freelancers find work, consolidate opportunities across platforms, and build a unified AI training portfolio they control. We make specialized AI training work easier to track, apply for, and grow into a durable freelance career.

About this role
OpenTrain is recruiting for a Materials Science AI Model Evaluation Expert to help benchmark advanced AI systems against real-world materials discovery workflows. This role combines deep materials and semiconductor expertise with hands-on evaluation of AI-generated scientific work. You will translate atomic-scale engineering challenges into structured, verifiable test problems and help define the standards used to measure model performance.

What you will do
You will map materials discovery workflows into discrete scientific subprocesses and evaluation tasks. You will convert engineering challenges into scenarios with defined inputs, constraints, and verified reference solutions. You will create scoring rubrics and validation rules for stoichiometry, thermodynamics, and stable simulation parameters, then review step-by-step AI reasoning traces to diagnose model failures. You will also help scope domain-specific data generation, synthetic physics pipelines, and fine-tuning strategies. The work includes technical discussions about thin-film deposition, etch, planarization, packaging, and semiconductor architectures.

Required skills
You should have a PhD or Master's degree in Materials Science, Applied Physics, Chemical Engineering, Microelectronics, or a related discipline. Deep expertise in atomic-scale materials engineering, including ALD, CVD, PVD, plasma etch, CMP, 3D packaging, or advanced memory and logic architectures, is required. You should have hands-on familiarity with Density Functional Theory, Molecular Dynamics, or Kinetic Monte Carlo simulation setups, along with the ability to formulate open-ended scientific workflows into structured problems with clear ground-truth criteria. Strong written and verbal communication skills are important for technical and business workshops.

Helpful background
Experience with materials discovery lifecycles, scientific benchmarking, computational physics or chemistry, and model reasoning evaluation can help you contribute effectively. Familiarity with Materials Studio is also relevant to this work.

Why work with OpenTrain
OpenTrain gives freelancers one place to manage AI training opportunities instead of rebuilding proof of work on every platform. A stronger OpenTrain profile helps you show credible experience, discover roles that match your skills, and turn AI training and data-labeling work into a long-term portfolio.