Remote NLP Information Extraction Engineer

Das ist der Job

Ability to document complex guidelines clearly and explain technical concepts to diverse stakeholders.

Darum lohnt es sich

This includes defining sampling strategies, managing annotation teams, conducting quality assurance, and resolving ambiguous cases. • Evaluate extraction model performance using metrics such as precision, recall, and F1 score.

Job Title: Information Extraction Specialist Location: Remote (Worldwide) Job Summary: An Information Extraction Specialist is responsible for identifying, extracting, structuring, and validating relevant data from unstructured and semi-structured sources such as documents, reports, web content, databases, and multimedia files.

The role involves applying natural language processing (NLP), machine learning models, rule-based systems, and data processing techniques to convert raw information into structured, usable datasets.

Responsibilities • Design and implement information extraction pipelines for diverse document types, including legal contracts, medical records, financial reports, news articles, and technical documentation. • Oversee the creation of high-quality training datasets for extraction models.

Analyze model errors, identify root causes, and iterate on guidelines, training data, or model architecture to improve results. • Evaluate and implement information extraction tools and platforms (open-source and commercial).

Develop scripts and workflows to automate aspects of the extraction pipeline. • Adapt extraction systems to new domains or document types, rapidly acquiring the necessary domain knowledge to create accurate guidelines.

Requirements • Minimum of 5 years of experience in Information Extraction, Natural Language Processing, Computational Linguistics, or relating fields. • Experience with Python for data analysis and NLP tasks.

Familiarity with NLP libraries such as spaCy, NLTK, Hugging Face Transformers, or Stanford CoreNLP. • Proven experience designing annotation schemas and guidelines for complex extractions tasks. Ability to anticipate edge cases and create clear, unambiguous instructions. • Deep understanding of evaluation methodologies for extraction tasks.

Experience calculating and interpreting precision, recall, F1, and other relevant metrics. • Strong problem-solving skills with ability to analyze model errors, identify patterns, and propose data-driven solutions. • Excellent written and verbal communication skills in English.