Research Scientist - Computational Mathematics (Scientific Coding / AI Evaluatio
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 highly analytical and research-driven individual with a strong background in Computational Mathematics to contribute to advanced AI evaluation initiatives.
In this role, you will design and solve research-grade quantitative problems, supporting the development and evaluation of next-generation AI systems. You’ll work at the intersection of scientific computing, mathematical modeling, and AI reasoning, contributing to high-impact projects with leading AI organizations.
Responsibilities:
Quantitative Problem Design and Solutioning:
- Design and develop research-level or graduate-level mathematical problems involving scientific computing and programming (Python)
- Define clear problem structures, including categories, tags, and difficulty levels
- Solve complex problems using rigorous mathematical and computational methods, ensuring accuracy and logical consistency
Quality Assurance & Collaboration:
- Actively participate in two-tier reviews, meticulously evaluating both accuracy of problems and solutions.
- Collaborate effectively with reviewers and team leads, demonstrating a proactive approach to incorporating feedback, refining content, and enhancing overall quality promptly.
Commitments Required: 8 hours per day with an overlap of 4 hours with PST.
Employment type: Contractor assignment (no medical/paid leave)
Duration of contract: 4 weeks
Location: Bangladesh, Brazil, Colombia, Egypt, Ghana, India, Indonesia, Kenya, Nigeria,Turkey, Vietnam
Selection process: Home Assignment
Requirements
- PhD or PhD Candidate in Computational Mathematics, Applied Mathematics, or related field
- Strong background in numerical linear algebra, computational mechanics, or scientific computing
- At least one peer-reviewed publication in a relevant domain
- Proficiency in Python for scientific computing (e.g., NumPy, SciPy, or similar)
- Strong analytical thinking and problem-solving skills
- Ability to clearly document complex mathematical reasoning and solutions