Mathematics / Statics Subject Matter Expert (Master / PHD)

4 semanas atrás

Aracaju, Brasil Innodata Inc. Tempo inteiro

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 RoleAt 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 Mathematics Subject Matter Expert 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 ResponsibilitiesCreate 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 toReview 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 CriteriaMaster'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. #J-18808-Ljbffr

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