Join a Fortune 500 multinational project in Canada as a.Take the lead in developing innovative solutions and driving key technology initiatives.
Develop train and deploy machine learning models on.C...Show moreLast updated: 30+ days ago
Promoted
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freelance.caToronto, Canada
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CalabrioON, CA
Remote
Full-time
Quick Apply
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Remote
Full-time
Quick Apply
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Full-time
Quick Apply
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Quick Apply
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Machine Learning Engineer
Company 1 - The Manufacturers Life Insurance CompanyToronto, Ontario
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Full-time
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Machine Learning Engineer
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Full-time
This individual will also play a vital role in enhancing data from sales analytics to gain insights into customer behavior, market trends, and sales performance.
By harnessing the power of Databrick...Show moreLast updated: 30+ days ago
This role offers fulltime or contract engagement with 100% remote flexibility. Join a Fortune 500 multinational project in Canada as a Machine Learning Enginner !
Take the lead in developing innovative solutions and driving key technology initiatives.
Send your application to and become a key member of the clients dynamic team.
Responsibilities :
Develop train and deploy machine learning models on AWS .
Collaborate with crossfunctional teams to gather requirements define project goals and design scalable machine learning architectures.
Conduct data preprocessing feature engineering and model evaluation to ensure highquality and reliable models.
Implement and optimize machine learning algorithms and pipelines.
Explore and experiment with generative AI techniques including large language models to solve complex problems.
Monitor and maintain deployed models ensuring performance scalability and reliability in production environments.
Stay uptodate with the latest advancements in machine learning generative AI and proactively propose innovative solutions to enhance existing systems.
Requirements :
Bachelors or advanced degree in Computer Science Engineering or a related field.
Strong experience in machine learning engineering with a focus on developing and deploying models in production environments.
Proficiency in using AWS tools and services for machine learning.
Solid understanding of deep learning architectures natural language processing ( NLP ) and generative AI models.
Proficiency in Python and experience with relevant libraries and frameworks such as TensorFlow PyTorch or Keras .
Experience with data preprocessing feature engineering and model evaluation techniques.
Familiarity with MLOps practices version control and CI / CD pipelines for machine learning .
Strong problemsolving skills and the ability to work on complex projects independently or collaboratively.
Excellent communication skills with the ability to convey complex technical concepts to both technical and nontechnical stakeholders.