# Materials Science Analyst

**Company:** [Gramian Consulting Group](null/companies/kANY7hHLXDH7fUqyifRLmf.md)
**Location:** Remote
**Workplace:** remote
**Employment type:** Contract
**Department:** Talent Solutions

[Apply for this job](null/view/fef1e4ce-1f10-46b9-9b52-74296575c0f4)

## Description

**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.

**Role Overview**

We are looking for a materials science professional to contribute to an advanced AI research project focused on building rigorous STEM coding datasets. The role combines **materials science expertise, Python-based scientific computing, and AI evaluation**, with a focus on creating well-structured scientific problems, implementing verified solutions, and developing tests that accurately distinguish correct from incorrect model outputs.

**Responsibilities**

**Design scientific coding tasks** with one main problem and at least 3 logically connected sub-problems.

Implement verified **Python solutions** with complete unit test coverage.

Create discriminative test cases that distinguish correct from incorrect AI-generated outputs.

Perform quality control checks using the Central Task Platform (CTP), including Tier 1 structure checks and Tier 2 quality rubrics.

Revise tasks and solutions based on QC feedback.

Optimize tasks against Pass@K evaluation criteria across multiple LLM judges, including GPT, Gemini, and Nemotron.

Validate scientific correctness, determinism, well-posedness, and expected outputs.

Maintain a low rework rate and high first-submission quality.

Participate in project reviews, feedback sessions, and standups during required overlap hours.

**CONTRACT:** Freelance / Contractor

**COMMITMENT:** Full-time commitment; overlap requirements to be confirmed

**LOCATIONS:** Remote; eligible locations to be confirmed

**PROCESS:** Not specified

## Requirements

**Design scientific coding tasks** with one main problem and at least 3 logically connected sub-problems.

Implement verified **Python solutions** with complete unit test coverage.

Create discriminative test cases that distinguish correct from incorrect AI-generated outputs.

Perform quality control checks using the Central Task Platform (CTP), including Tier 1 structure checks and Tier 2 quality rubrics.

Revise tasks and solutions based on QC feedback.

Optimize tasks against Pass@K evaluation criteria across multiple LLM judges, including GPT, Gemini, and Nemotron.

Validate scientific correctness, determinism, well-posedness, and expected outputs.

Maintain a low rework rate and high first-submission quality.

Participate in project reviews, feedback sessions, and standups during required overlap hours.