As one of the key members on the Demand Intelligence team that is part of AI group, you'll take ownership of the design and implementation of our client's consumer-facing search. The key objective of the AI Group is to build a Semantic Knowledge Graph to help personalize bespoke learning experiences for students and help educators create unique course content.
The charter for the Demand Intelligence team is to focus on delivering value to students and educators by enabling search intelligence and demand-side data products. This team will be building a Semantic Search engine using NLP and ML driven search mechanisms for the long-tail distribution and consumption of our document corpus. This also includes building user cohorts, an inference engine to infer intent, behavior, usage, trends, and economic demand curves powering content discovery and recommendations, pricing, and other applied data science initiatives.
Our client's Staff Engineer is a technical leader who provides mentorship for team members, drives key projects, and participates in the continuous improvement of our software systems. We expect you to thrive in a fast-paced, high-growth environment, and adapt to ever-changing business needs. Check out these videos to learn more about our engineering culture, and our company mission.
· You'll contribute to building semantic search capabilities ground-up by developing entity disambiguation models, lexers, parsers, lemmatization schemes, stemmers, recommenders and relevance models.
· You'll improve the relevancy and functionality of our consumer-facing search by combining the capabilities of Elasticsearch with the application of Machine Learning over our vast dataset.
· You'll be designing and implementing high performance and scalable search systems, indexing over 16 million pieces of content in every conceivable format for every academic subject.
· You'll work with our engineering, product and design teams to build new features, tools and functionality with AWS, Docker, React, Elasticsearch, Tensorflow, and other tools in our stack.
· You'll leverage ML, NLP and advanced IR techniques to help solve problems beyond user-facing search - these include recommendations, duplicate / copyright detection, and natural language understanding applications.
Are you our next Staff ML Engineer, Search Sciences?
· You have 8+ years of experience building search relevancy ranking and boosting algorithms, and leveraging NLP, ML, and semantics to deliver high-precision search experiences.
· You have 2-3 years of recent experience with search and indexing engines such as Elasticsearch, Solr, or Lucene and graph databases such as Neo4j.
· You have 5+ years of programming experience in at least two of the following languages such as Java, Python, Scala, Go, PHP.
· You have exposure to advanced approaches in information retrieval (IR) such as vector-space and feature-based retrieval models, deep learning based embedding approaches, and clustering/classification for IR, query expansion, question-answering.
· You have earned an advanced (MS or above) degree in Computer Science or STEM field.
· You have code you can share through a project website or GitHub repo.
· You have experience in leading or mentoring less-experienced engineers.
Our client is an online learning library where you can access over 20 million course-specific study resources contributed by a community of students and educators. You'll find practice problems, study guides, videos, class notes, and step-by-step explanations for every subject you're studying — from economics to literature, biology to history, accounting to psychology, and everything in between. We help you quickly find what you need so you can learn deeply.