Role Description
As an Algorithm Engineer - Search & Recommendation, you will own and drive the end-to-end improvement of AlloFresh's product search experience. You'll design, build, and deploy search, ranking, and recommendation models that power how customers discover and buy groceries on AlloFresh.
You'll help launch foundational improvements to our search retrieval and ranking pipeline and partner closely with our Data Science and Commercial teams to drive measurable business impact and elevate the shopping experience.
If you're passionate about applying advanced algorithms to solve real-world problems at scale, this role is one of the highest-leverage opportunities at AlloFresh, search is how our customers shop, and you'll own it.
Main Responsibilities
- Own the entire search pipeline end-to-end: retrieval, re-ranking, and personalization
- Design and optimize hybrid lexical-semantic retrieval pipelines to improve precision and recall
- Build and deploy multi-task ranking layers that balance conversion, diversity, long-term user retention and business needs, integrating real-time signals such as promotions, surge and stock availability
- Develop personalised ranking layers and user behaviour models leveraging historical orders, search patterns, preferences, and contextual features.
- Write production-grade backend code; build, deploy, and maintain the services that serve search results to users at scale
Requirements
- Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related quantitative field
- 4–5 years of experience in software engineering, with a strong focus on search and/or recommendation systems
- Solid software engineering skills in Python and Golang, with experience building production backend services (APIs, microservices, data pipelines)
- Strong proficiency in Elasticsearch or equivalent search engines, including index design, query DSL, custom scoring, and performance tuning.
- Experience designing, building, and deploying large-scale ranking or recommendation systems in production, including neural ranking or personalization models in consumer products (e-commerce, food delivery, marketplace, ads, or similar).
- Experience building search systems (including multilingual contexts), with understanding of query processing techniques such as intent classification, entity extraction, and spell correction.
- Hands-on experience building large-scale ranking or recommendation systems in consumer products (e-commerce, food delivery, marketplace, ads, or similar).
- Proven track record of improving search or recommendation performance through data-driven experimentation (e.g., A/B testing) and delivering measurable business impact.
- Passionate about technical challenges, self-driven and able to deliver project requirements on time
- Good communication skills in Bahasa and English, both written and verbal.
