Machine Learning Engineer

Granify

Alberta, CA / Edmonton, CA
  • Job Type: Full-Time
  • Function: Data Science
  • Post Date: 01/19/2021
  • Website: granify.com
  • Company Address: 10248 - 106 Street, Edmonton, AB, T5J 1H7

About Granify

Granify automatically maximizes revenue for online retailers by identifying shoppers that aren’t going to buy and changing their mind - before they leave the site - by harnessing the power of real-time big data and machine learning.

Job Description

We’re searching for a Machine Learning Engineer to join our platform team. While focusing on machine learning development, with our small, agile team you'll get a chance to design, build, and improve each part of our tech stack, while providing guidance and technical direction. 


This position is full-time in Edmonton, AB, Canada. We welcome local applicants, as well as any Canadian citizens, permanent residents, or eligible international applicants willing to relocate.

 

What You'll Work On

 

As a Machine Learning Engineer with Granify you’ll:

 

  • Research, design and prototype intelligent systems with the aim of enhancing online shopper experience.
  • Productionize research prototypes into fully-fledged AI software that are ready to be delivered to our clients.
  • Participate in active maintenance and code reviews in a large codebase, suggesting and implementing changes as appropriate.
  • Keep up-to-date with the latest papers in artificial intelligence and machine learning to propose solutions for real problems in e-commerce.
  • Build infrastructure to support the evolution of our shopper interaction toolset.
  • Mentor other engineers, participate in code reviews, and share knowledge.
  • Troubleshoot, test, and debug to your heart’s content.

 

You Are…

 

  • Passionate about finding elegant solutions to complex technical problems.
  • Committed to mastery and craftsmanship in your work.
  • Team-focused and people-centric, able to give feedback as well as receive it.
  • Curious, constantly looking for better ways to build things and excited to learn about emerging technologies.
  • Positive and personable - we're all tackling these challenges together!
  • Able to communicate with clarity and brevity.

 

Fundamentals:

 

  • BSc (MSc or PhD preferred) in Computer Science, Machine Learning, Artificial Intelligence, Statistics, Mathematics, Engineering, Physics, or a related discipline, with (at minimum) graduate-level courses in machine learning, or equivalent practical experience.
  • Strong research experience in machine learning, preferably in one or more of the following (in no particular order): reinforcement learning, natural language processing, recommendation and/or ranking systems, deep generative models, representation learning, AI interpretability, domain generalization, meta-learning, computer vision, deep neural network architectures.
  • Proficient in deep learning frameworks like Tensorflow, PyTorch, etc. and scientific computing packages like NumPy. Able to implement an algorithm as described in an academic paper using these frameworks in quality code.
  • Strong computer science background, with experience in object-oriented programming, systems design, data structures and algorithms. Proficient in Python and/or C/C++, with an interest in learning new languages.
  • Familiarity with source control (Git) and Unix systems, including shell scripting.
  • Good intuition for applying AI theory to make business-oriented products with minimal guidance.
  • Communicate to introduce honesty and clarity (avoiding buzzwords and jargon) to experts in multiple disciplines. Demonstrate a mature understanding of the current possibilities and limitations of AI research.

 

Bonus points if you have expertise in:

 

  • Evidence of academic publications in machine learning and/or computer science research.
  • Experience in online advertising and/or marketing analytics, behavioural targeting and/or web analytics.
  • Experience working in an Agile software development environment.
  • Experience in using cloud solutions, preferably AWS.
  • Experience in distributed and/or parallel programming.
  • An active GitHub repository.

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Disclaimer: Local Candidates Only
This company does NOT accept candidates from outside recruiting firms. Agency contacts are not welcome.