Job Description
The role involves designing and implementing machine learning systems, particularly recommendation and ranking models, to extract insights from large-scale structured and unstructured data, supporting Affinity's relationship intelligence platform within a collaborative, fast-paced environment.
Key Responsibilities
- Design, develop, and deploy AI systems for information retrieval, ranking, and recommendation tasks.
- Manage the full machine learning lifecycle from ideation to production, including feature engineering, model selection, deployment, and evaluation.
- Translate business requirements into robust machine learning solutions and system designs.
- Build and optimize recommendation and ranking infrastructure, evolving from off-the-shelf models to customized solutions.
- Work on complex data extraction, storage, and retrieval problems involving structured and unstructured data.
- Collaborate with cross-functional teams to develop scalable, high-performance data processing and ML operations systems.
Requirements
- At least 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 and 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 such as 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.
Benefits & Perks
Health benefits covering both employee and dependents, including extended health benefit premiums and flexible personal sick days
Retirement planning through an RRSP plan
Learning and development support with an annual education budget and comprehensive L&D program
Wellness support including monthly reimbursements for home internet, meals, and wellness memberships or equipment
Team connection activities such as virtual team-building activities and socials
Ready to Apply?
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