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Engineer • sudbury on
MLOps Engineer
Motion RecruitmentON, Canada- Promoted
Engineer
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Keller Executive SearchON, CA- Promoted
Manufacturing Engineer
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vTech SolutionON, CanadaCivil Engineer
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LaborintosOntario, CA- Promoted
Project Engineer
Lactalis CanadaK0C, ON, Canada- Promoted
- New!
Emulation Engineer
Intellectt IncOntario, Canada, CanadaMLOps Engineer
Motion RecruitmentON, Canada- Full-time
We are looking for an experienced MLOps Engineer in Canada to join a growing startup focused on building a lip-syncing tool to break down language barriers in advertising and the film industry.
Join a high-impact analytics and machine learning team focused on building scalable, data-driven solutions to improve operational efficiency, pricing strategy, and customer intelligence across international logistics and supply chains. This role is ideal for someone who thrives in a fast-paced, data-rich environment and is passionate about solving complex business problems using advanced modeling and analytics.
Required Skills and Experience :
- 3+ years of experience in data science, machine learning, or applied statistics
Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, PyTorch / TensorFlow)
Experience with cloud platforms (e.g., AWS, GCP) and ML Ops tools
Solid grasp of SQL and data manipulation in large datasets (Spark, BigQuery, or similar)
Strong understanding of statistical modeling, time series forecasting, and / or optimization algorithms
Prior work with pricing models, logistics, or real-time analytics is a strong plus
Excellent communication skills and ability to translate business needs into technical solutions
Develop and deploy predictive models for pricing, demand forecasting, and route optimization using large-scale, real-time data.
Analyze customer behavior patterns to drive retention, segmentation strategies, and lifetime value prediction.
Design and implement scalable data pipelines and production-ready ML systems in collaboration with data engineering teams.
Conduct A / B testing and causal inference to evaluate model impact and guide strategic decision-making.
Collaborate cross-functionally with product, operations, and engineering teams to identify opportunities for automation and efficiency.
Continuously monitor model performance , retrain as needed, and ensure alignment with evolving business objectives.
The Offer :
LI-CT2