Crossing Hurdles

Machine Learning Engineer

Crossing Hurdles

Remote · Contract

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Experience
Any
Salary
USD 30 – USD 100 / hour
Openings
1
Posted
2 hours ago
Work mode
Work from home
Eligibility
Candidates who can work remotely from Canada and are available for a contract role with a weekly commitment of 10 to 40 hours.
Resume
Required to apply

Job description

Role Overview

We are looking for a Machine Learning Engineer for a contract assignment that can be done remotely from Canada. The position offers an hourly rate of $30 to $100 and requires a commitment of 10 to 40 hours per week.

What You’ll Do

  • Build, train, and release machine learning models with TensorFlow and Scikit-Learn to address practical business challenges.
  • Prepare datasets end to end by cleaning data, transforming it, and creating features that support strong model performance.
  • Work closely with data scientists, data engineers, and business analysts to convert business needs into scalable ML solutions.
  • Track model performance in production, assess results, and make improvements to keep systems accurate, efficient, and dependable.
  • Record the model development workflow and explain technical findings clearly to both technical and non-technical stakeholders.
  • Keep up with current machine learning research and techniques, and apply useful innovations to improve outcomes.

What We’re Looking For

  • Advanced hands-on experience with TensorFlow and Scikit-Learn across the full model development and deployment lifecycle.
  • Strong capability in data preprocessing, including missing value treatment, outlier handling, and feature selection.
  • Proven ability to design and deliver machine learning systems that are suitable for production use.
  • Good understanding of model choice, evaluation measures, and performance optimization methods.
  • Ability to work autonomously in a remote setting and deliver results in a fast-moving, deadline-oriented environment.

Application Process

  • Submit your application through the provided quick-apply process.
  • Watch for follow-up communication by email.
  • Proceed through resume review and the interview stage.

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