Lead design, architecture, and operation of backend services for recommendations
Architect large-scale data pipelines (e.g., Spark) for features inputs
Collaborate with ML engineers to productionize models and interfaces
Drive ML/AI systems like vector search for recommendations
Implement observability (metrics, logging, tracing, dashboards)
Mentor engineers and define patterns to accelerate new use cases

🎯 Requirements

5+ years of software engineering in production backend services
Backend and distributed systems at scale; high-throughput, reliable
Proficient in Python
Cloud-native architecture with AWS; container orchestration (Kubernetes)
Data-driven decision making and A/B testing
Querying data models: Postgres, MySQL, data warehouses, Redis, vector DBs

🎁 Benefits

Generous health, welfare, and wellbeing benefits
Equity and annual bonus plans
Hybrid work option in US locations
Professional growth and mentorship
AI guidelines and privacy protections

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