MLOps Engineer

Motion Recruitment; Ontario; On-site; CAD 90,000 - 120,000; Full time

Job summary

A growing startup in Canada is seeking an experienced MLOps Engineer to join their analytics and machine learning team. The role involves developing predictive models, designing scalable data pipelines, and collaborating with cross-functional teams to enhance operational efficiency. Ideal candidates will thrive in a fast-paced environment, leveraging their expertise in Python and machine learning to solve complex business challenges.

Qualifications

• 3+ years in data science, machine learning, or applied statistics.
• Experience with cloud platforms and ML Ops tools.

Responsibilities

• Develop and deploy predictive models for pricing and demand forecasting.
• Collaborate with teams to identify automation opportunities.

Skills

Python

Communication

Statistical Modeling

Education

Degree in Computer Science

Degree in Statistics

Degree in Engineering

Tools

AWS

GCP

SQL

Spark

BigQuery

scikit-learn

XGBoost

PyTorch

TensorFlow

Job description

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

Degree in Computer Science, Statistics, Engineering, or related field (graduate degree preferred)

What you will be doing :

• 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.

Contribute to building a robust ML platform , including best practices, documentation, and reusable components.