Machine Learning Intern

Location: Remote / Concord, MA
Date Posted: 10-24-2017
Are you passionate about Machine Learning (ML), Deep Learning, and Natural Language Processing? We are looking for talented Machine Learning Interns to join our dynamic and collaborative startup team to work on the cutting edge of AI technology.

At BigR.io, our top and innovative scientists are revolutionizing the field of Artificial Intelligence (AI). Our expert Data Science team is led by MIT and Caltech PhDs, specializing in Deep Learning Architectures (CNNs, RNNs, LSTMs, GRUs, and Bidirectional Networks and DNNs with Attention mechanisms) and Machine Learning approaches (NLP, Reinforcement Learning, and Clustering Algorithms). As a result, these capabilities make BigR.io a firm the Fortune 1000 can rely on.


About You:
  • Undergraduate/Graduate student in Engineering, Computer Science, Computer Engineering, Physics, and Economics.
  • Excellent knowledge of data structures, algorithms and modern OOP techniques.
  • Experience working with real-world noisy and/or large-scale datasets.
  • Excellent knowledge of one or more of: machine learning, signal processing, statistical modeling, time-series analysis, optimization.
  • Solid understanding of statistical analysis.



Responsibilities:
  • Design, build, and deploy Machine Learning algorithms for advanced analytics in a variety of potential applications including finance, technology, e-Commerce, music and entertainment, social network and media, and voice-enabled Conversational AI platforms.
  • Perform exploratory data analysis and visualizations on multivariate data sets.
  • Work closely with our data engineering team to productionize.




Beneficial Experience:
  • Development experience with Python.
  • Experience with Matlab and/or R.
  • Experience developing software in a Unix programming environment.
  • Preferred familiarity with Relational and Non-Relational databases (NoSQL).
  • Preferred Experience with one of the well-known neural network libraries, such as Keras, TensorFlow, Theano, or Caffe.
  • Preferred Experience with NLP and unstructured data parsing.
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