Scientific Chemistry, Python, AI Evaluation

🔥 14 hours ago

🇧🇩 Bangladesh – Remote

⏳ Contract/Temporary

🟡 Mid-level

🟠 Senior

🔙 Backend Engineer

👻 Ghost score 12%

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Logo of Gramian Consulting

Gramian Consulting

2 - 10 employees

Founded 2025

💼 Consulting

📦 Logistics

📣 Marketing

Consulting • Logistics • Marketing

Gramian Consulting is a remote-first consulting firm that connects engineering and data/AI talent with organizations through talent augmentation, recruiting, dedicated teams, and contractor management. The firm provides Data & AI services including LLM training and fine-tuning, AI agents and assistants, MLOps, and AI infrastructure, and it offers mentorship and education programs for career readiness, interview preparation, and international market orientation. Rooted in hands-on engineering and recruiting experience, Gramian helps clients scale technical teams and extract business value from AI while developing individual talent.

📋 Description

• Design scientific coding tasks consisting of one main chemistry problem and at least 3 logically connected, progressively structured sub-problems • Develop verified golden solutions in Python with complete unit test coverage • Create discriminative test cases that distinguish correct from incorrect AI-generated outputs • Execute quality control validation through the Central Task Platform (CTP), including Tier 1 structural checks and Tier 2 quality rubrics • Iterate on task specifications, implementations, and test cases based on QC feedback • Optimize tasks to meet Pass@K evaluation criteria across multiple LLM judges, including GPT, Gemini, and Nemotron • Ensure scientific correctness, determinism, well-posedness, and adherence to project quality standards • Maintain high first-submission quality and minimize rework, targeting consistent L1 approval • Participate in review meetings, feedback sessions, and project standups during required overlap hours

🎯 Requirements

• Master's degree or PhD in Chemistry • Strong Python programming skills with experience in scientific computing • Experience using scientific Python libraries such as NumPy, SciPy, SymPy, or relevant domain-specific tools • Ability to formulate rigorous scientific problems with clear constraints and expected outputs • Experience writing or implementing scientific solutions with unit tests and deterministic outputs • Prior experience in AI data annotation, scientific research, or scientific writing • Familiarity with LLM evaluation frameworks, coding benchmarks, or AI-generated code assessment • Published research or academic project experience involving chemistry or another STEM discipline

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