Machine Learning Software Engineer

Machine Learning Software Engineer

Stardog is the world's leading Knowledge Graph platform for the Enterprise. Turn data into knowledge faster and easier. Stardog lets you query, search, and analyze enterprise data, wherever it is, using scalable, cutting-edge Knowledge Graph technology.

We've been actively working on adding machine learning capabilities to Stardog, and are looking for someone to help us take it to the next level.
If you're interested in natural language processing, deep learning, probabilistic graphical models, and recommender systems, this might be the job you've been dreaming about!

Responsibilities
  • Research and develop algorithms to analyze large scale (un)structured data
  • Design and develop high-performance, data-driven components for our distributed database
  • Implement complex data ingestion pipelines
  • Deploy and operationalize machine learning models

Requirements:
  • 5+ years programming experience, ideally in Java
  • Strong computer science fundamentals, with advanced knowledge of data structures, algorithms, and software design
  • Experience on applying machine learning and natural language processing techniques to real world datasets
  • Interest in recent scientific developments, with an eye for practical applications
  • Knowledge of Vowpal Wabbit, Theano/Keras, GATE/UIMA, Lucene/ElasticSearch, and similar frameworks
  • Ability to work in a distributed team mainly communicating over email, chat, and phone
  • Experience with graph technologies or databases is a plus

We have offices in Arlington, VA and Boston, MA. Remote working is also possible for qualified candidates.

Our culture is based on engineering excellence, mutual respect, collegiality in all things, rigor in design, research, implementation, and testing. We care deeply about work-life balance and productivity in the short and long run. In sum, if you remove the unnecessary, the distracting, and the tedious, what you're left with is a healthy 40 hour week full of wins.

We are committed to creating a diverse environment and are proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
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