Senior Applied AI/ML Scientist
Job description
About the role
Faire is a technology wholesale platform built on the belief that the future is local. Independent retailers around the globe collectively represent a multi-hundred-billion-dollar wholesale market that has historically been fragmented and offline. At Faire, we are using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe. Picture your favorite boutique in town - we help them discover the best products from around the world to sell in their stores. With the right tools and insights, we believe that we can level the playing field so businesses can grow and local communities can thrive. We are looking for smart, resourceful and passionate people to join us as we power the shop local movement. If you believe in community, come join ours. This Senior Applied AI/ML Scientist role is central to our Retailer Growth Data team, where you will own the development and deployment of AI and machine learning systems that directly activate new retailers and deepen engagement on our platform. You will be responsible for designing and implementing solutions that span paid marketing optimization, search intelligence, and advanced audience targeting while maintaining a strong focus on measurable business impact. The role requires close collaboration with cross-functional partners to translate ambiguous product challenges into robust data science roadmaps and production-ready models. You will drive the strategic execution of computer vision, natural language processing, and reinforcement learning initiatives aimed at automating content creation and personalizing the retailer journey. Ultimately, your work will influence how Faire leverages data to empower local businesses and redefine wholesale marketplaces.
Key facts
What you'll do
Drive data science vision, strategy, and execution within Retailer Growth, using AI/ML solutions to activate and engage more retailers on the platform.
Work with cross-functional stakeholders to develop end-to-end product solutions that align with business objectives and technical feasibility.
Extract deep behavioral insights using AI to automate AEO content creation and personalize the user landing experience at scale.
Optimize marketing capital allocation through sophisticated targeting and bidding optimization strategies that improve efficiency and return.
Implement rigorous experimentation and causal inference frameworks to quantify the impact of growth levers and inform decision-making.
Engineer scalable solutions for complex challenges inherent to two-sided marketplace dynamics, ensuring reliability and performance.
Leverage LLM-based methods for programmatic content generation to support Answer Engine Optimization initiatives across the funnel.
Develop and maintain production-grade models for LTV prediction, search relevance, and ad bidding in a high-growth environment.
Collaborate closely with product managers and engineers to translate business requirements into machine learning features and evaluation metrics.
Explore novel reinforcement learning approaches to create fast feedback loops for offer and landing page optimization.
Partner with data engineering to ensure data quality, feature reliability, and efficient model deployment workflows.
Conduct deep dives into behavioral data to uncover patterns that drive retailer acquisition, activation, and retention.
Champion best practices in model interpretability, fairness, and privacy across all solutions delivered by the team.
Mentor junior scientists and contribute to the growth of the data science community within Faire.
Present findings and recommendations to both technical and non-technical audiences, influencing strategic direction with data-backed insights.
Requirements
3+ years of industry experience using machine learning to solve real-world problems.
Experience with relevant business problems in e-commerce, including marketplace dynamics and advertiser behavior.
Experience with relevant technical methods such as LTV modeling, NLP, LLMs, causal ML, and bidding optimization.
Strong programming skills in Python and related data science ecosystems.
An excitement and willingness to learn new tools and techniques in a fast-paced environment.
The ability to design and implement ML solutions without supervision while adhering to best practices.
Strong communication skills and the ability to work effectively in a highly cross-functional team.
Proficiency with SQL and data manipulation at scale is mandatory for deriving insights and building features.
Experience with cloud platforms and MLOps tooling for deploying models into production is required.
A proven track record of delivering data-driven impact in a production setting is essential.
Commitment to writing clean, maintainable, and well-documented code for long-term maintainability.
Understanding of ethical considerations in ML and dedication to responsible AI practices.
Willingness to collaborate closely with product, engineering, and analytics stakeholders across time zones.
Nice to have
Highly recommended: Master's or PhD in Computer Science, Statistics, or related STEM fields.
Previous experience in paid marketing, and/or growth team focusing on SEO and AEO optimization.
Previous experience in LLMs and programmatic content generation.
Practical notes
This is a full-time position based in Kitchener-Waterloo, ON, or Toronto, ON.
Eligible candidates must be authorized to work in Canada without sponsorship for this role at this time.
Salary range is $180,000 to $247,500 per year, with equity and benefits eligibility. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market conditions, and location.