Job Description
A Senior Machine Learning Engineer at Affinity is responsible for designing, developing, and deploying scalable AI systems, particularly recommendation and ranking models, to extract insights from large datasets and enhance the company's relationship intelligence platform.
Key Responsibilities
- Design, develop, and deploy AI systems for recommendation and ranking 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.
- Build and optimize recommendation and ranking systems using techniques like learn-to-rank, collaborative filtering, and content-based filtering.
- Work on information extraction, storage, and retrieval problems for structured and unstructured data.
- Collaborate with cross-functional teams to build high-scale data processing and ML operations systems.
Requirements
- Minimum of 5 years of experience in software engineering and/or Machine Learning experience in applying machine learning in production.
- Hands-on experience developing recommendation and ranking systems at scale, using techniques such as Learn-to-rank (LTR) algorithms, including RankNet, LambdaRank, or similar approaches.
- Experience with collaborative filtering and content-based filtering, reranking strategies, and hybrid search implementations.
- Solid understanding of machine learning techniques, including clustering and decision forests.
- Experience with serving ML models for streaming and batch inference at scale.
- Experience with vector databases such as Milvus or Weaviate, or graph databases like Neo4j.
- 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, including A/B testing and tracing for AI applications.
Benefits & Perks
Compensation/salary range: 140,000 to 200,000 CAD
Work schedule: Flexible personal sick days
Work environment perks: Virtual team-building activities and socials
Health Benefits: Extended health benefit premiums covered for employee and dependents, wellness memberships, home internet, and meals reimbursements
Retirement Planning: RRSP plan
Learning Development: Annual education budget and comprehensive L&D program
Ready to Apply?
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