Build RAG systems: Architect, prototype, and deploy RAG pipelines, combining vector search, hybrid retrieval, reranking and contextual compression techniques.
Build LLM powered agent systems: Contribute to design and orchestration of multi-agent LLM systems using community frameworks and custom orchestration layers.
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) to build robust, high-scale systems that underlie all of our data processing and ML Operations.

2+ years of experience in software engineering and/or Machine Learning experience in applying machine learning in production.
Hands on experience with LLM applications in production including prompt engineering and utilizing frameworks for online and offline evaluation
Experience with LLM assisted search, such as query understanding and augmentation, text2sql, and entity extraction
Experience with vector or graph databases
Experience with document chunking, embedding models, and context window optimization
Familiarity with metadata-based retrieval and re-ranking strategies
Hands on experiences with model evaluation metrics (e.g. perplexity, hallucination rate, factual consistency)
Familiarity with data security, versioning, and MLOps principles.

We cover both you and your dependents' extended health benefit premiums and offer flexible personal & sick days to support your well-being.
We offer an RRSP plan to help you plan for your future.
We provide an annual education budget and a comprehensive L&D program.
We reimburse monthly for things like home internet, meals, and wellness memberships/equipment to support your overall health and happiness.
Virtual team-building activities and socials to keep our team connected, because building strong relationships is key to success.

AI Engineer, AI Platform

Key skills