Principal Machine Learning Engineer
Back River Search
- San Francisco, CA
Our client is an artificial intelligence company that organizes and analyzes text-based data sources and generates analyst-grade natural language summaries for a variety of industries. Our objective is to help our customers understand the world around them -- whether it is emerging geopolitical events, development of a product line or area of research, or monitoring a portfolio of companies’ financial performances.
- Ensure the quality of our core machine learning platform - developing best practices and tooling in the team.
- Propose and lead long-term investments in machine learning, to solve problems at or beyond the state-of-the-art.
- Develop presentations and technical discussions to evangelize and teach both within Primer and without.
- Deliver high impact improvements to our core platform, and for specific client focussed products.
- M.Sc. or Ph.D. in computer science, statistics, machine learning, or other quantitative field.
- 8+ years of professional experience developing and deploying data and algorithm driven software products.
- Deep understanding of key ML algorithms and when and how to apply them.
- Experience with NLP and machine learning tools and libraries such as numpy, SpaCy, NLTK, Scikit-learn, Tensorflow, Keras.
- Specific experience with NLP tasks such as event and topic detection, relation extraction, summarization, entity recognition, document classification and knowledge base generation.
- Understanding of computational complexity and strategies for scaling and distributing large computations.
- Experience in distributed computing, preferably including working with AWS/Azure, the Elastic stack, and Docker.
- Passionate about driving the performance of machine learning algorithms towards the state of the art, and in challenging us to continually improve what is possible.
Tuesday, June 19, 2018