Opportunity brief
Responsibilities:
- Design and build pipelines for ingesting data from APIs, documents, files, web sources, images, videos, audio, and other structured or unstructured sources.
- Develop multilingual NLP pipelines for knowledge graphs and information retrieval.
- Transform extracted information into knowledge graphs and other analytical methods.
- Apply statistical learning, machine learning, embeddings, clustering, anomaly detection, and graph analytics.
- Develop production-grade Python services and APIs for model inference, data processing, and downstream product integration.
- Design evaluation datasets and measure extraction accuracy, quality, false positives, confidence calibration, latency, and throughput.
- Implement monitoring and error-analysis workflows for models and data pipelines.
- Collaborate with analysts, product managers, data engineers, and software engineers to translate requirements into reliable analytical capabilities.
- Document data assumptions, model limitations, lineage, and evaluation methodology.
- Support deployment across cloud, on-premises, and hybrid environments where required.