Data Scientist (ML Engineer)

Kibbi Technologies Inc.; Toronto; On-site; CAD 120,000 - 140,000; Full time

Benefits offered by this job

Competitive rewards

Hub offices 3x a week

Paid time off

Learning & development

Parental leave

Volunteering opportunities

ERGs

Job summary

Flywheel is seeking a Data Scientist (ML Engineer) to design, implement, and operate machine‑learning systems that autonomously bid and allocate spend across thousands of brands in production, in real time.

You will work with Python and Google Cloud tools (Cloud Run, Vertex AI) to productize features, experiment with models, and align with evolving generative and agentic AI layers. Collaboration across cross‑functional teams and a culture that values growth and impact.

Qualifications

• 5+ years as data scientist or engineer collaborating with data scientists
• Experience processing terabytes of data daily
• Productionization and monitoring experience
• Experience in retail media, digital advertising, or ecommerce is a plus
• Strong knowledge of ML pipelines and optimization

Responsibilities

• Build ML systems that decide how thousands of brands spend budgets in production
• Design and analyze experiments to derive actionable insights
• Improve Perpetua's advertising engine through data-driven optimization
• Define the role of reinforcement learning vs classical optimization and LLM reasoning
• Contribute to best practices, design documents, and recruitment

Skills

Python

ML Engineering

Data Science

Pandas

PyTorch

XGBoost

BigQuery

GCP

Reinforcement Learning

LLM concepts

Tools

Vertex AI

BigQuery

Cloud Run

Keras

PyTorch

Job description

Agency

Flywheel

Job Function

Data and Analytics

Job Subfunction

Data Engineering

Job Description

About Flywheel

Flywheel’s suite of digital commerce solutions accelerate growth across all major digital marketplaces for the world’s leading brands. We give clients access to near real-time performance measurement and improve sales, share, and profit. With teams across the Americas, Europe and APAC, we offer a career with real impact, endless growth opportunities and the support you need to be the best you can be.

The Opportunity

Perpetua is the retail media platform within the Flywheel Commerce Network, built for the challenger brand; the operator who cannot out spend the category leader and has to out execute instead. Advertisers set goals based on strategy and Perpetua’s always on optimization executes the tactics.

As a Data Scientist (ML Engineer), on the Perpetua team, you will design, experiment with, and ship the machine learning systems that decide how thousands of brands spend their advertising budgets across retail media. This is the engine that takes autonomous action on the customer’s behalf. It is not a model that produces recommendations for someone else to act on, but the system that sets bids and allocate spend in production, in real time, against each advertiser’s goals. Your work runs live across thousands of customers worldwide.

Our team primarily works with Python and the Google Cloud Platform suite of products like Cloud Run and Vertex AI to productize cutting‑edge data features. We are currently working on developing a scalable advertising bidding platform that enables advertisers to implement custom and versatile bidding strategies including but not restricted to maximizing advertising sales, dominating top‑of‑search placements, optimizing for total sales, incremental sales, new‑to‑brand purchases, organic rank, etc. Increasingly, this work sits alongside a newer layer of generative and agentic AI; LLM‑based reasoning that plans, explains, and reacts to natural language goals. Knowing where classical optimization is the right tool and where the generative layer adds leverage is part of the craft on this team.

What You Will Do

Work across retail media (starting with Amazon) to understand the intricate relationships between bids, placement, conversion, and sales, and turn that understanding into systems that optimize advertising autonomously on the customer’s behalf.

Design, Implement, and Analyze experiments for deriving Actionable Insights.

Analyze advertising performance data to improve the core strategies that power Perpetua's advertising engine.

Help define how Perpetua’s machine‑learning optimization works alongside the emerging generative and agentic layer, deciding where reinforcement learning and classical optimization are the right tools, and where LLM‑based reasoning meaningfully improves how the platform plans and explains its decisions.

Support the growth of the team by contributing to activities for establishing best practices, recruitment, and authoring design documents.

Who You Are

5+ years of experience as a data scientist or engineer working with data scientists

Strong experience with algorithms and data pipelines processing terabytes of data per day

You have experience taking concepts from inception through to production and ongoing monitoring and enhancements

Experience in retail media, digital advertising, or e‑commerce is an asset

You have worked in organizations with cross‑functional teams of ~5 people, solving hard problems collaboratively and working tightly with your immediate team members and across the organization

Working knowledge of reinforcement learning and linear/non‑linear optimization is a strong asset, given how central these techniques are to the bidding engine

Curiosity about applied LLMs and agentic systems, and comfort using modern AI‑assisted development tools (such as Claude Code) as part of how you build

Able to create and make changes to traditional ML models, including but not limited to Linear regression, XGBoost and Logistic regression

Competent in training and evaluating models using mainstream data science tools including but not limited to sklearn, Pandas, keras and/or PyTorch

Experience in cloud native ML training platforms like BigQuery ML or Snowpark

Working at Flywheel

We are proud to offer all Flywheelers a competitive rewards package and unparalleled career growth opportunities and a supportive, fun and engaging culture.

We have office hubs across the globe where team members can go to feel productive, inspired, and connected to others - team members go into Hub Offices 3x a week

Competitive paid time off, including annual leave plus paid public holidays

Great learning and development opportunities

Benefits that help you live your best life

Parental leave and benefits

Volunteering opportunities

If you’re looking to connect with teammates on a topic of inclusion and identity, chances are there’s an ERG for that.

So you know: The hired candidate will be required to complete a background check

Learn more about us here: Life at Flywheel

The Interview Process

Every role starts the same, an introductory call with someone from our Talent Acquisition team. We will be looking for company and values‑fit as well as your professional experience; there may be some technical role‑specific questions during this call.

Every role is different after the initial call, but you can expect to meet several people from the team 1:1 and there might be further skill assessments in the form of a Take Home Assignment/Case Study Presentation or Pair Programming/Live Coding exercise depending on the role. In your initial call, we will walk you through exactly what to expect the process to be.

Inclusive Workforce

Flywheel Commerce Network’s goal is to create a culture where all individuals of all backgrounds feel comfortable in bringing their authentic selves to work. We want all people to feel included and empowered to contribute fully to our vision and goals. Flywheel Commerce Network is an Equal Opportunity Employer and participates in E-Verify. All applicants will receive fair consideration for employment. We do not discriminate based upon race, color, religion, sex, sexual orientation, age, marital status, gender identity, national origin, disability, or any other applicable legally protected characteristics in the location in which the candidate is applying.

If you have any accessibility requirements that would make you more comfortable during the application and interview process, please let us know at [e-mail] so that we can support you.

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We leverage AI technology to streamline our hiring workflow, though all candidate decisions are made by our Talent Acquisition Team. This position is for an existing vacancy.

$120,000 - $140,000 CAD

$120,000 - $140,000 CAD