Own the full ML lifecycle: Take projects from ideation to production, including feature engineering, model selection, deployment, and model observability and evaluation.
Translate business needs into ML solutions: Gather product requirements and translate them into robust ML system design requirements.
Build recommendation and ranking systems: Architect and launch ranking and recommendation infrastructure from scratch, initially via integrated off-the-shelf models, and evolving to targeted and customized solutions in the long term.
Solve complex problems: Work on a variety of information extraction, information storage and information retrieval problems for both structured and unstructured data.
Collaborate cross-functionally: Partner with cross-functional (product, infra, data engineering, and software engineering) teams to build robust, high-scale systems that underlie all of our data processing and ML Operations.
Requirements
5+ years of experience in software engineering and/or Machine Learning experience in applying machine learning in production.
Hands-on experience developing ranking or recommendation systems from scratch, deployed at scale using techniques such as learn-to-rank, explainable recommendations.
Strong understanding of machine learning techniques, including clustering and decision trees.
Experience with serving ML models for streaming and batch inference at scale.
Experience with vector or graph databases.
Proficiency in Python and modern ML frameworks (PyTorch, Scikit-learn, or similar).
Track record of building maintainable, testable, and production-grade codebases.
Experience with observability tools for online and offline model evaluation, A/B testing, and tracing for AI applications.
Tech Stack
Python
PyTorch
Scikit-Learn
Benefits
Health Benefits: We cover both you and your dependents' extended health benefit premiums and offer flexible personal & sick days to support your well-being.
Retirement Planning: We offer an RRSP plan to help you plan for your future.
Learning & Development: We provide an annual education budget and a comprehensive L&D program.
Wellness Support: We reimburse monthly for things like home internet, meals, and wellness memberships/equipment to support your overall health and happiness.
Team Connection: Virtual team-building activities and socials to keep our team connected, because building strong relationships is key to success.