Found Description
Location
In Canada, Mistplay follows a 2 days/week in-office hybrid model in Toronto (400 University Ave) & Montreal (1001 Blvd. Robert-Bourassa).
Responsibilities
- Design, build, and operate machine and data infrastructure solutions for training models.
- Build real‑time inference systems to operate and serve models in a real‑time production environment.
- Develop high usability and accuracy feature platform capabilities for generating, backfilling and storing user‑level features.
- Create high‑accuracy low‑latency feature serving layers and preprocessing solutions to support online serving of models.
- Build platform abstractions and golden paths: Airflow DAG templates, CI/CD pipelines, CLI/SDKs, cookie‑cutter repositories that shepherd models from notebooks to production predictably.
- Implement end‑to‑end observability: data and feature freshness checks, drift/quality gates, model performance/latency SLO...