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Full Stack Developer (Scala/Java) At Cerebri AI

Location: Toronto, Ontario

Job Description

As a Full Stack Developer (Scala/Java), you will play an integral role in the development of our flagship AI product offerings for enterprise. You will be part of a small, focused team working in fast paced environment.

Responsibilities

  • Developing reactive applications that manage large datasets in conjunction with machine learning models trained against that data.
  • Maintaining automated test coverage against all code you produce.
  • Contributing to design discussions related to product.
  • Building and maintaining Continuous Integration (CI) pipelines to maximize efficiency and ensure quality in the development process.
  • Learning about the latest and greatest advancements in machine learning and data engineering while simultaneously looking for opportunities to apply them in our products.
  • Meeting hard product deliverable deadlines set in a rapidly evolving startup environment.

Qualifications

  • Excellent Java programming skills with two (2) years or more experience.
  • Working knowledge of functional programming basics.
  • Machine learning and/or ETL experience with Apache Spark.
  • Working knowledge of Relational databases (Postgres, Oracle), Distributed clusters (Hive, Ignite), Graph databases (OrientDB, Neo4j) etc.
  • Experience setting up automated tests that provide full code coverage and building/maintaining Continuous Integration (CI) pipelines (e.g. Jenkins, Travis CI, CircleCI).
  • Experience operating in a “full stack” type role, with the ability to be flexible with the tasks you work on day-to-day.
  • Familiarity with Agile methodology and Scrum framework for managing processes.
  • Proficiency in managing software projects in Git.
  • Excellent verbal and written communication skills.
  • Bachelor's Degree in Computer Science (or related area).

Nice to haves...

  • Experience with Scala, AngularJS, React, D3, Lightbend Reactive Platform (Play and Akka), HTML, CSS, Grunt,
  • Understanding of basic machine learning model configurations (e.g. Random Forest, Naïve Bayes, Neural Networks) and common API frameworks that can be used to deploy them (e.g. Spark MLlib, Python scikit-learn, Tensorflow).
  • Experience in deploying statistical models for use in applications (e.g. Naive Bayes, Gaussian Mixture Models, Hidden Markov Models, etc.).
  • Familiarity with common neural network configurations and the problems they can be used to solve.
  • Experience with the Atlassian suite (JIRA, Confluence, BitBucket).
  • Any other related experience with Big Data, artificial intelligence, natural language processing, machine learning and/or deep learning, predictive analytics