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.
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