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Machine Learning Engineer

Flashfood13 days ago
Remote
Toronto, ON
Mid Level

Top Benefits

Competitive salary
Comprehensive health, dental, and vision benefits
Opportunities for growth and learning within a high-impact mission

About the role

Who we are:
Flashfood is a marketplace app that connects grocery retailers with shoppers to sell food nearing its best-before date at a deep discount. Our mission is to reduce food waste and make food more affordable. By keeping great food out of landfills and helping people access nutritious meals for less, we’re driving meaningful impact for both people and the planet.

How it works:

Download the Flashfood app and create an account

Browse deals at nearby partner grocery stores
Purchase items through the app

  • Pick up purchases from the Flashfood Zone in-store

Role Overview:
We’re looking for a Machine Learning Engineer to help power decision-making, personalization, and automation at Flashfood. Reporting to the Director of Data, you’ll work closely with data analysts, engineers, and product managers to design and deploy machine learning models that improve customer experience, enhance retailer insights, and drive operational efficiency.

This is a hands-on role focused on turning raw data into intelligent, scalable systems that enable better business outcomes. You’ll play a key role in building the next generation of ML infrastructure and shaping how predictive technologies are used across the business.

Responsibilities:

Model Development & Deployment

Design, train, and evaluate machine learning models to support business goals (e.g., recommendation systems, dynamic pricing, demand forecasting, user segmentation)

Collaborate with data scientists, analysts, and engineers to operationalize models using tools such as Databricks, MLflow, and Spark
Develop robust pipelines to deploy models into production, ensuring scalability, reliability, and performance

  • Monitor model performance over time, retrain as needed, and improve accuracy and impact

Data Engineering & Infrastructure

Collaborate with data engineering teams to build reliable, well-structured datasets

Contribute to ML platform and pipeline improvements (CI/CD for ML, observability, feature stores)

  • Ensure that models are integrated seamlessly into our core products and tools

Collaboration & Enablement

Partner with Product, Marketing, and Operations teams to understand challenges and identify ML opportunities

Present insights and model outcomes to cross-functional stakeholders in a clear and actionable way

  • Contribute to team best practices around model development, experimentation, and documentation

Qualifications:

3–5+ years of experience in machine learning or data science roles, with experience deploying models into production

Proficient in Python and SQL; experience with ML libraries such as scikit-learn, PyTorch, or XGBoost
Experience working with cloud data environments (e.g., Snowflake, Databricks, AWS)
Familiarity with ML and data pipeline tools (e.g., MLflow, Airflow, dbt) as well as MLOps best practices
Strong problem-solving skills and ability to communicate technical concepts to non-technical audiences

  • Passion for purpose-driven work and a desire to reduce food waste and make food more accessible

What We Offer:

Competitive salary

Comprehensive health, dental, and vision benefits
Opportunities for growth and learning within a high-impact mission

  • Collaborative, remote-first team culture

The chance to help solve one of the planet’s biggest sustainability challenges

About Flashfood

Retail Groceries
51-200

Flashfood is on a mission to feed families, not landfills. Our app connects shoppers with fresh produce, meat and other groceries at up to 50% off. By partnering with retailers across North America, we offer nutritious staples at affordable prices and reduce the amount of food going to landfills.

Flashfood is a certified B Corp remote-first company currently partnered with more than 2,000 stores across North America. Since launch, Flashfood has diverted more than 100 million pounds of food from landfill and saved its shoppers more than $250 million on their groceries.