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Machine Learning Engineer
Machine Learning EngineerHifyre • Canada
Machine Learning Engineer

Machine Learning Engineer

Hifyre • Canada
Il y a 14 jours
Type de contrat
  • Temps plein
Description de poste

About Us :

Hifyre provides market intelligence for the cannabis industry, analyzing retail data to help

industry stakeholders understand market dynamics. Our models power product recommendations, sales forecasting, and market analysis for both internal operations and external customers. You’ll work closely with other like-minded, skilled individuals to create dynamic & cutting-edge products, supporting our larger retail parent, The FIKA Company.

We're looking for a machine learning engineer to develop models that drive business decisions, someone who can design statistically sound experiments and deploy models to production.

What you'll do :

You'll handle everything from data collection through production deployment :

  • Model Development & Feature Engineering : Build and improve recommendation systems, sales forecasting models, and product forecasting. Create features from large retail datasets, including collecting new data sources when needed.
  • Experimentation & AB Testing : Design and analyze AB tests for product recommendations. Use statistics to measure impact and inform product decisions.
  • Pipeline & Infrastructure : Help maintain our market intelligence infrastructure, build model-specific data pipeline in Airflow, deploy models via Flask APIs, and manage batch prediction systems.

What you'll bring :

  • Strong Python skills : ML model development, data pipeline automation
  • Machine learning experience : Experience with scikit-learn and building production ML applications (recommendation systems, time series forecasting, geospatial modeling)
  • Statistical foundation : Hypothesis testing, experimental design, AB testing methodology, and statistical significance analysis
  • Feature engineering : Build features from large retail datasets
  • SQL proficiency : Working with data warehouses and large datasets
  • Production deployment & cloud experience : Deploying models to production, working with orchestration tools, and experience with AWS services
  • Software engineering practices : Version Control, code review, testing, deployment workflows
  • Nice to have :

  • Experience with Airflow (or similar orchestration tools like Dagster, Matillion)
  • Familiarity with time series forecasting tools (Prophet, statsmodels)
  • Experience with geospatial analysis libraries (GeoPandas)
  • Web scraping experience (Playwright, Scrapy, Selenium)
  • Prior experience with Redshift or other cloud data warehouses
  • Familiarity with the cannabis industry or regulated retail environments
  • What we offer : The Work

    You'll be part of a small data science team supporting a growing business where models

    directly drive both operations and revenue. Your work will have immediate, visible impact.

    The Challenges

    Building recommendation systems at scale, forecasting for cannabis retail markets, designing statistically rigorous experiments, and maintain production ML infrastructure.

    What’s in it for you

    Work remotely within Ontario!

    Comprehensive benefits - your health is important to us. Our benefits include health, dental, mental health support and more!

    Our organization provides structured incentive plans as a supplementary component of total compensation, designed to reward individual and team performance!

    Generous vacation and wellness time off - we offer our employees 3 weeks PTO - effective in your first year and we encourage you to use it!

    Team member discount with several cannabis retailers!

    Hifyre values the diversity of the people it hires and serves. Inclusion to us means fostering a workplace in which individual differences are recognized, appreciated, respected, and responded to in ways that fully develop and utilize each person’s talents and strengths.

  • Thank you for your interest and application, only those selected for next steps will be contacted. This application may be evaluated using AI technology as part of our process. Final hiring decisions are made by people.
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