Research and Recommendations of Senior Machine Learning Backend Engineer

Job description

About the Role: Senior Machine Learning Backend Engineer - Research & Recommendations the employer, a leading e-commerce platform in the MENA region serving over 68,000 merchants, is looking for a Senior Machine Learning Backend Engineer for its AI team. This position is full-time based and requires experience. The role focuses on owning the online systems that turn catalog changes into ranked results for shoppers, including search, retrieval, recommendations, data flow and experimentation. Role Context and Impact the employer's AI team is developing a self-owned discovery suite for its marketplaces and department stores, featuring hybrid lexical and vector search, Arabic-first query understanding, and combined learned classification between search and recommendations. While data scientists manage saliency and classification models, this role is responsible for the platform that ensures these models are fast, up-to-date, reliable, and shippable. The distribution of work is approximately half online service, one-third streaming data, and the rest is for integration into product surfaces. This position is part of the ML Platform team, collaborating daily with Research Data Scientists and Ranking Lead. Key Responsibilities Online Service: Establish and operate query and recommendation delivery systems, including retrieval, result merging, filtering and caching. Adhering to strict latency budgets, the P95 targets double-digit milliseconds for searching while typing. Design great degradation mechanisms to keep the service stable when it encounters Patterns or vector paths slowdowns or interruptions. Implement the experience infrastructure, including shadow traffic, A/B mapping, guardrail metrics, and undo capabilities. Data Flow: Develop pipelines to capture change data from source systems to search indexes and feature stores, with measured freshness. Ensure that embeds stay up to date for new and updated items. Implement non-stop re-indexing for multi-million document collections. Build feature scoring systems to turn production traffic into training data for classification models. Integration: Integrate changes into the backends for product teams and customers, including new endpoints, shards, and experience tags. Collaborate with product engineering teams on reviews, release windows, and production ownership. Operability: Create and maintain monitoring, alerting, and operational logs for deployed systems. Participate in on-call rotation of owned systems. Required Experience: Candidates must possess relevant professional experience. WORK ENVIRONMENT This is a full-time position located. The role involves working within the ML Platform team and collaborating closely with research data scientists and the ranking lead

Requirements

• · This position is full-time based and requires experience
• · Experience Required Candidates must have relevant professional experience

Skills