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Masters / PHD In Physics

Masters / PHD In Physics

Innodata Inc.Francisco Beltrão, Paraná, Brazil
Há 13 dias
Descrição da vaga

Innodata (NASDAQ : INOD) is a leading data engineering company. With more than 2,000 customers and operations in 13 cities around the world, we are an AI technology solutions provider of choice for 4 out of 5 of the world’s biggest technology companies, as well as leading companies across financial services, insurance, technology, law, and medicine.

By combining advanced machine learning and artificial intelligence (ML / AI) technologies, a global workforce of subject matter experts, and a high-security infrastructure, we’re helping usher in the promise of AI. Innodata offers a powerful combination of both digital data solutions and easy-to-use, high-quality platforms.

Our global workforce includes over 5,000 employees in the United States, Canada, United Kingdom, the Philippines, India, Sri Lanka, Israel and Germany. We’re poised for a period of explosive growth over the next few years.

About the Role :

At Innodata, we’re working with the world’s largest technology companies on the next generation of generative AI and large language models (LLMs). We’re looking for smart, savvy, and curious subject matter experts.

We are seeking a Masters / PHD In Physics with exceptional writing and analytical skills to join our AI / ML data team. In this role, you will help train advanced Large Language Models (LLMs) by producing, curating, and reviewing high-quality educational and technical mathematics content. Your expertise will directly shape the way AI systems understand, explain, and reason about fundamental and advanced mathematical concepts.

Key Responsibilities :

Create high-quality, accurate, and pedagogically sound content in mathematics, including :

Conceptual explanations

Problem sets and solutions

Theoretical summaries and derivations

Research abstracts and technical writing

Collaborate with AI researchers and engineers to :

Review and refine mathematics-related model outputs

Identify and fill conceptual gaps in LLM training data

Build datasets across various mathematics domains (e.g., Algebra, Calculus, Geometry, Linear Algebra, Probability, Statistics, Number Theory, Discrete Math, etc.)

Provide feedback to improve LLM performance in reasoning, solving, and communicating mathematical content

Eligibility Criteria :

Master's or PhD in Mathematics or a closely related discipline (MS with exceptional experience may be considered)

Strong background in theoretical and / or applied mathematics

Excellent technical and academic writing skills

As part of the project, you are required to complete the English language assessment.

  • The assessment is mandatory & non-billable
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Master • Francisco Beltrão, Paraná, Brazil

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