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The ML Engineer will architect and build personalization and recommendation systems, design user preference algorithms, collaborate with teams, and improve systems from research to production.

Build and run backend systems spanning the SvelteKit app, Postgres/Redis/ClickHouse data stores, Python ML inference services, and Kubernetes clusters. Own design, monitoring, metrics, and incident response. Implement durable execution for long workflows, improve public APIs, and add enterprise features like ACLs and audit logs.

Lead enterprise onboarding and enablement for Krea: run demos, lead workshops, design production workflows, gather customer feedback, and relay product insights to improve the product.