About this role
Are you passionate about text mining, information retrieval, and machine learning? Do you enjoy designing algorithms, building models, and moving metrics by applying these techniques to solve real world problems that improve the lives of hundreds of millions of professionals? As you a relevance engineer that loves to build and implement relevance based products end-to-end? Then, this is your dream job!
LinkedIn was built to help professionals be more productive and successful in their careers. Every day millions of people use our products to make connections, discover opportunities, and gain insights. Our global reach means we get to make a direct impact on the world’s workforce in ways no other company can. We’re much more than a digital resume – we transform lives through innovative products and technology.
At LinkedIn, we regularly process semi-structured content in the 340+ million member profiles and the content they create on LinkedIn, such as posts, comments, job descriptions, group discussions, news articles that are shared, slideshows, images, and videos. The content relevance builds recommendations for LinkedIn members which are surfaced to members in several of LinkedIn’s products, including pulse, groups, and slideshare. As a Sr/Staff software engineer working on IR, ML, and NLP, you’ll be building our next generation content understanding, recommendation, and response prediction algorithms and models that power content relevance algorithms.
Responsibilities:
Design and develop algorithms, models, and pipelines that power content recommendations based on Machine Learning and Natural Language Processing (NLP) techniques and consume data inferred from member profiles, user generated content, and behavioural data.
Produce deliverable results and see them through from development to production.
Interact and work with teams located in multiple sites.
Company:
Qualifications:
Basic Qualifications:
Masters Degree in Computer Science, Information Retrieval, Machine Learning, Natural Language Processing, or related discipline.
Expertise in one or more of the following domains: recommender systems, machine learning, information retrieval, information extraction (POS, N/E tagging with HMMs/CRF etc), feature extraction, text classification, etc
Solid experience in Java, C++, or another object-oriented language.
Preferred Qualifications:
Ph.D. in Computer Science, Information Retrieval, Machine Learning, Natural Language Processing, or related discipline.
Worked with web-scale traffic and data.
Experience solving “big data” problems using clustered computing systems, such as MapReduce, Dataflow, Hadoop/Cosmos/Spark, Lucene/SOLR, Storm/Samza, etc. Think terabytes to petabytes of data.
Experience with developing and designing consumer-facing products.
Published work in academic conferences or industry circles.
Educational level:
Master Degree
How to apply:
Please mention NLP People as a source when applying