Shape Homebase’s machine learning foundations with MLflow, feature stores, and real-time inference from the Toronto hub. Build platforms serving every data and AI feature. This Data and ML Platform Engineer role focuses on turning machine learning proofs of concept into production systems. You will evolve feature stores, strengthen MLflow practices, and build serving layers for models and data. Your work includes Python, SQL, Spark, Delta, Databricks, gRPC, and LLM latency and cost visibility. Key Responsibilities:

Grow feature store and MLflow foundations Partner with data science on production systems Move batch workloads toward real-time inference Make LLM latency and cost visible Share effective AI-assisted engineering practices Requirements:

Experience with MLflow and feature stores is beneficial Robust Python and SQL skills Hands-on Spark and Delta experience Experience with container infrastructure AI fluency and experimentation with engineering tools Help deliver reliable machine learning infrastructure through serving systems, platform engineering, and practical collaboration with data science.

📌 Machine Learning Infrastructure Engineer (Toronto)
🏢 Homebase
📍 Toronto