PhDs in Physics, Chemistry or Biology

Role Overview: As a highly analytical and detail-oriented scientific expert at Innodata, your primary responsibility will be to support AI training and model evaluation initiatives. Ideal candidates for this role are PhDs in Physics, Chemistry, Biology, or Computer Science with a strong passion for research, critical thinking, and applying domain-specific knowledge to cutting-edge AI applications. You will play a crucial role in contributing to the development and improvement of AI systems, including large language models (LLMs) and other machine learning pipelines, by creating, curating, and evaluating scientific datasets, validating model outputs, and providing domain-specific insights. Key Responsibilities: - Create, review, or annotate high-quality scientific content and datasets for training or evaluating AI systems. - Perform quality assurance on model-generated outputs to ensure scientific accuracy, clarity, and alignment with domain knowledge. - Analyze and interpret AI behavior within the context of domain-specific tasks and error patterns. - Assist in developing guidelines for scientific content generation and annotation. - Collaborate with internal engineering, data, and linguistic teams to maintain accuracy and consistency across projects. - Conduct domain-specific research and synthesize findings to drive model improvements. - Identify and address issues related to ambiguity, bias, or misrepresentation in scientific content. Qualifications: - PhD in Physics, Chemistry, Biology, Computer Science, or a closely related scientific discipline. - Strong analytical skills and the ability to apply theoretical knowledge to real-world datasets and AI systems. - Familiarity with scientific writing standards, peer-reviewed publishing, or lab-based research methodology. - Attention to detail and the capability to critically evaluate scientific content for accuracy and clarity. - Excellent writing, editing, and communication skills. (Note: No additional details about the company were provided in the job description.) Role Overview: As a highly analytical and detail-oriented scientific expert at Innodata, your primary responsibility will be to support AI training and model evaluation initiatives. Ideal candidates for this role are PhDs in Physics, Chemistry, Biology, or Computer Science with a strong passion for research, critical thinking, and applying domain-specific knowledge to cutting-edge AI applications. You will play a crucial role in contributing to the development and improvement of AI systems, including large language models (LLMs) and other machine learning pipelines, by creating, curating, and evaluating scientific datasets, validating model outputs, and providing domain-specific insights. Key Responsibilities: - Create, review, or annotate high-quality scientific content and datasets for training or evaluating AI systems. - Perform quality assurance on model-generated outputs to ensure scientific accuracy, clarity, and alignment with domain knowledge. - Analyze and interpret AI behavior within the context of domain-specific tasks and error patterns. - Assist in developing guidelines for scientific content generation and annotation. - Collaborate with internal engineering, data, and linguistic teams to maintain accuracy and consistency across projects. - Conduct domain-specific research and synthesize findings to drive model improvements. - Identify and address issues related to ambiguity, bias, or misrepresentation in scientific content. Qualifications: - PhD in Physics, Chemistry, Biology, Computer Science, or a closely related scientific discipline. - Strong analytical skills and the ability to apply theoretical knowledge to real-world datasets and AI systems. - Familiarity with scientific writing standards, peer-reviewed publishing, or lab-based research methodology. - Attention to detail and the capability to critically evaluate scientific content for accuracy and clarity. - Excellent writing, editing, and communication skills. (Note: No additional details about the company were provided in the job description.)