Senior ML Backend Engineer - Search & Recommendations
Key Skills for This Role
Full Job Posting
Requirements
- 5+ years building backend or platform systems in production.
- 2+ years operating a production search engine (Elasticsearch, OpenSearch, Solr, Typesense, Vespa or similar): index lifecycle, analyzers, reindexing at scale, debugging relevance issues with data scientists.
- Low-latency services under real traffic, and the ability to explain where the p95 goes.
- Streaming ingestion: Kafka, Debezium or similar change-data-capture, plus idempotent backfills.
- Strong Python. Comfortable shipping in TypeScript.
- Shipped changes through A/B tests and staged rollouts.
- Daily use of agentic coding tools such as Claude Code. We expect one engineer plus agents to cover what used to take a team.
Responsibilities
- Online serving
- Build and run query and recommendation serving: retrieval, score fusion, filtering, caching.
- Hold tight latency budgets, including double-digit-millisecond p95 for search-as-you-type.
- Design graceful degradation, so serving holds up when a model or vector path is slow or down.
- Build experiment plumbing: shadow traffic, A/B assignment, guardrail metrics, rollback.
- Streaming data
- Build change-data-capture from source systems into search indexes and feature stores, with measured freshness.
- Keep embeddings fresh for new and updated items.
- Run zero-downtime reindexing of multi-million-document collections.
- Build feature logging that turns production traffic into training data for ranking models.
- Integration
- Ship changes into product teams' backends and clients: new endpoints, cutovers, experiment flags.
- Work with product engineering teams on reviews, release windows and production ownership.
- Operability, throughout
- Monitoring, alerting, runbooks, and your share of on-call for what you ship.
About salla
Saudi SaaS e-commerce platform helping merchants in Saudi Arabia and the GCC build and manage online stores.
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