Job Description
A Senior Machine Learning Engineer at Affinity is responsible for designing, developing, and deploying AI systems that extract insights from large-scale structured and unstructured data, focusing on recommendation and ranking systems to enhance the company's relationship intelligence platform.
Key Responsibilities
- Design, build, and deploy AI systems for information retrieval, extraction, 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 scalable and robust ML solutions.
- Develop and launch ranking and recommendation infrastructure, evolving from off-the-shelf models to customized solutions.
- Collaborate with cross-functional teams to build high-scale data processing and ML operations systems.
- Solve complex problems related to structured and unstructured data for information extraction and retrieval.
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
Team connection activities such as virtual team-building activities and socials
Ready to Apply?
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