Machine Learning Engineer II — Real-Time ML Platform
Scribd, Inc.Role Overview
Scribd, Inc. is hiring a mid-level Machine Learning Engineer II — Real-Time ML Platform. This is a full-time role in Vancouver, British Columbia. Part of Scribd, Inc.'s Data Science hiring. Full responsibilities, required qualifications, and the apply link are listed in the description below.
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Job Description
A leading digital library is seeking a Machine Learning Engineer II to design and optimize high-impact ML systems serving millions of users. You'll engage in projects enhancing ML platforms and integrating models into the product experience, while enjoying a flexible work model and comprehensive benefits. Ideal candidates have solid ML engineering experience, proficiency in Python or Golang, and strong cloud knowledge. The position promises a salary range of CAD 131,500 to CAD 174,500, plus competitive equity ownership.
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Frequently Asked Questions
How do I apply for the Machine Learning Engineer II — Real-Time ML Platform position at Scribd, Inc.?
Use the Apply button above to submit your application directly to Scribd, Inc.. Most applications take less than 5 minutes if your resume and contact details are ready, and you'll be routed to the employer's official application system to finish.
Where is the Machine Learning Engineer II — Real-Time ML Platform position at Scribd, Inc. located?
This position is based in Vancouver, British Columbia. Scribd, Inc. has not indicated remote or hybrid options for this role, so candidates should plan for on-site work.
What does a Machine Learning Engineer II — Real-Time ML Platform at Scribd, Inc. earn?
Scribd, Inc. has not disclosed a salary range in this posting. Many employers share specifics later in the interview process; you can also ask during a recruiter screen if compensation transparency is important to you.
When was the Machine Learning Engineer II — Real-Time ML Platform role at Scribd, Inc. posted?
This role was posted on March 18, 2026 (81 days ago). It's still listed as actively hiring; we re-confirm openings against the source system multiple times per day and remove closed roles.
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