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 Strong 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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Machine Learning Infrastructure Engineer in Toronto employer: Homebase
Homebase is an exceptional employer that fosters a collaborative and innovative work culture, where Principal Engineers can thrive in shaping the future of payroll, scheduling, and HRM solutions. With a strong emphasis on employee growth, you will have access to mentorship opportunities and the chance to work with cutting-edge AI technologies in a supportive environment. Located in a vibrant area, Homebase offers unique advantages such as flexible work arrangements and a commitment to work-life balance, making it a rewarding place to advance your career.
