Machine Learning Research Engineer


Marketmuse Inc.’s M4 Lab is seeking a Research Engineer to help create the next generations of content analytics and content generation technologies. This role blends production software development and research in deep learning, information theory, machine learning, knowledge representation, and computational linguistics. The engineer will work on natural language processing systems that try to understand the semantics, intent, and topical structure of vast amounts of web content. This role requires extensive knowledge and experience in architecting and developing data intensive applications.

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 (the MarketMuse Montreal Machine Monograph Lab) will be a hub for our advanced machine learning and data sciences teams working on cutting-edge R&D to improve our systems’ quality of content understanding, knowledge representation, and machine learning powered content generation assistance tools. Our software also helps our clients optimize or create content ranging from short blog posts to long whitepapers.


  • Design and implement reliable distributed data pipelines
  • Design and implement scalable machine learning solutions geared towards solving natural language processing, knowledge representation, and natural language generation problems
  • Create parallelized and/or distributed versions of existing algorithms
  • Research, design and develop novel algorithms
  • Collaborate with research scientists, architects, software developers, 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

Required Skills

  • Experience with architecting data intensive applications
  • Experience with data mining or machine learning applications
  • Experience writing software in one or more languages such as Python, Scala and/or similar. Experience working with data structures, algorithms and software design
  • Knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, tools and environments (such as Apache Beam, Hadoop, Spark, Pig, Hive, MapReduce, Flume)
  • Experience with fast prototyping
  • Experience working effectively with software engineering teams
  • Mentor others in achieving their career growth potential

Required Education and Experience Level

  • MS in Computer Science, Computer Engineering, 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 engineering experience with respect to ML/DL/NLP/NLG
  • At least 1 year of distributed or highly threaded software development experience

Preferred But Optional Skills

  • Experience with workflow tools like Airflow, Luigi, etc.
  • Hands-on experience implementing new research ideas with a neural network training framework such as Tensorflow, Keras, or PyTorch
  • A PhD in machine learning
  • Experience with academic machine learning research
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