APTPUO-Fall -DTIF

Description

Posting limited to:

Date Posted (YYYY/MM/DD):

Applications must be received
BEFORE (YYYY/MM/DD):

Expected Enrolment:

Approval date:

Number of credits:

Work Hours:

Hourly Rate:

The academic year starts on September 1 and ends on August 31.

These rates do not included vacation pay nor statutory pay.

These rates will be applied until a new collective agreement is ratified. Retro will be paid after the ratification.

Course type:

Posting type:

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Competence in second language:

Course

Schedule:

Requirements:

Priority will be given to applicants who are in the process of completing a PhD in Digital Transformation and Innovation, Computer Science, or Electrical Engineering. The applicant must possess a minimum of three years of industry experience in a senior or lead role as a machine learning engineer. They should have hands-on experience applying the latest MLOps techniques, such as continuous integration, model and data versioning, automated retraining, and model updating, specifically within the framework of an industry project.

Additionally, the applicant must have comprehensive experience with state-of-the-art, cloud-based machine learning development environments, including Amazon Sage Maker and Databricks Unified Analytics Platform. The applicant must be highly knowledgeable in the latest deep learning architectures, including CNNs, LSTMs, and transformers.

Additional Information and/or Comments:

An acceptable level of education and/or experience could be viewed as being equivalent to the educational required and/or demonstrated experience.