This is a fully remote position, open to applicants in Canada.

📋 Description

• Design, develop, and manage the online feature store — the real-time serving layer that provides ML features to production models with minimal latency and robust consistency guarantees.

• Create and sustain data pipelines (both batch and streaming) that compute, validate, and disseminate features from source systems into both online and offline stores.

• Collaborate on the data models and Postgres schemas that support real-time feature serving, focusing on optimizing query performance, data freshness, and scalability.

• Serve as a technical leader for feature store infrastructure; assist in enhancing quality, scalability, reliability, and observability for the systems that machine learning models rely on.

• Work closely with our Data Science, Analytics Engineering, Product Management, and Application Development teams to convert business needs into production-ready engineering solutions.

• Contribute to the mentorship of junior engineers.

• Help establish best practices and elevate standards through insightful code reviews and participation in technical design discussions.

⛳️ Requirements

• Over 5 years of software engineering experience, focusing on backend systems (Python is a must) and 2-3 years in MLOps.

• Extensive experience with relational databases (Postgres preferred) — including schema design, query optimization, and managing databases under production conditions.

• Proven experience in building and maintaining real-time inference systems.

• Understanding of the specific reliability and correctness requirements of ML-serving infrastructure (data freshness, training/serving skew, feature consistency).

• Familiarity with multi-service architectures and design patterns.

• Experience in Agile software development methodologies.

• Typically possesses a Bachelor's degree in Computer Science, Data Engineering, or a related field, or equivalent relevant experience.