Principal Deep Learning Natural Language Generation Researcher


The new MarketMuse Montréal Machine Monograph Lab (M4 Lab) is seeking a Research Scientist to help create the next generations of Natural Language Generation technologies. This is an applied research position where the researcher will work on generative deep learning models oriented to create context-aware draft content conditioned on existing semistructured data, for use in our clients’ content marketing. This role requires deep understanding of deep learning, information theory, computational linguistics, and hands-on experience with a modern deep neural training framework such as Tensorflow or PyTorch.

About Us

Marketmuse Inc. is a rapidly growing institutionally-backed content planning technology firm with offices in Montreal, Boston, and New York City. We are the premier provider of enterprise content planning technologies and are recognized as a leading technology for content marketing functions. MarketMuse’s new M4 Lab will be a hub for our advanced machine learning and data sciences teams working on bleeding-edge research to improve the quality of content our software helps our clients create, ranging from short blog posts to long whitepapers.


  • Apply quantitative, analytical, and creative skills to design, develop and test a Natural Language Generation system along with other team members, in an environment with many supporting technologies and users eager to provide corrective training data
  • As research project lead, you would be a Principle Investigator on bleeding edge research
  • Explore new research ideas with regard to NLG, formulate R&D projects, and architect scalable implementations
  • Research, design and develop novel algorithms
  • Collaborate with architects, software developers, data science management, and product management to design and program innovative strategic and tactical solutions that meet market needs with respect to functionality, performance, reliability, realistic implementation schedules, and adherence to development goals and principles
  • Gather and determine requirements for new features from internal colleagues
  • Develop and document intellectual property
  • Publish select scientific discoveries in academic journals or conferences

Required Skills

  • Experience with generative deep learning techniques in a text, language, or NLP domain
  • Deep understanding of models and techniques such as recurrent neural networks, seq2seq models, distributional semantics, attention mechanisms, and variational autoencoders
  • Experience with attention mechanisms, conditional language models, and RNNs
  • Hands-on experience implementing new research ideas with a neural network training framework such as Tensorflow, Keras, or PyTorch
  • Keep up to date on the latest research for deep learning for NLG, NLP, and summarization
  • Strong problem solving skills
  • Experience with fast prototyping and iterative experimentation
  • Experience working effectively with software engineering teams
  • Knowledge of information theory, multivariate calculus, and multilinear algebra solid enough to specify novel relevant deep learning and machine learning algorithms
  • Teach and mentor other ML-knowledgeable coworkers in advanced deep learning techniques
  • Excellent communication, teamwork, and technical writing skills

Desired Pluses

  • Experience with any of VAE-GANs, cGANs, or RL-GANs
  • Experience with neural corpus summarization

Required Education and Experience Level

  • PhD in Deep Learning, Machine Learning, Statistics, Computational Linguistics, or a very related field; other exceptional candidates with extensive ML/DL/NLP/NLG backgrounds may also be considered
  • At least 2 years of research experience in some combination of academia or industry with respect to ML/DL/NLP/NLG

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