Staff Software Engineer

October 17

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Logo of Fetch Rewards

Fetch Rewards

Mobile applications • Grocery Retail • Shopper Data

501 - 1000

💰 Debt Financing on 2022-04

Description

• What we’re building and why we’re building it. • Every month, millions of people use America’s Rewards App, earning rewards for buying brands they love – and a whole lot more. Whether shopping in the grocery aisle, grabbing a bite at the drive-through or playing a favorite mobile game, Fetch empowers consumers to live rewarded throughout their day. • Fetch is reshaping how brands and consumers connect in the marketplace. • Ranked as one of America’s Best Startup Employers by Forbes for two years in a row, Fetch fosters a people-first culture rooted in trust, accountability, and innovation. • At Fetch, we are on a mission to build the most comprehensive product catalog across every retailer in the U.S., and eventually the world. • Our catalog is the backbone of the Fetch platform, powering critical features such as personalization, relevance, search, and product matching. • We are seeking a Staff Software Engineer with deep expertise in building and scaling large, data-rich product catalogs.

Requirements

• 5+ years of experience building and maintaining large-scale, high-performance product catalogs or similar data-driven applications, with a strong focus on reliability, scalability, and accuracy. • Proven experience delivering software in a high-traffic production environment, with an emphasis on data quality, integrity, and operational excellence. • Strong proficiency in at least one of the following programming languages: Python, Go, Java, with the ability to write clean, efficient, and maintainable code. • Expertise in cloud-based distributed systems (AWS or similar), microservices architecture, and handling large-scale data ingestion and processing workflows. • Familiarity with machine learning techniques for data cleaning, enrichment, and classification tasks, such as entity resolution, named entity recognition, and image/text classification. • Strong understanding of data modeling and data structures, especially in building product catalogs with complex relationships between entities. • Experience with AdTech or systems that optimize and generate ad content using product metadata. • Experience using GenAI/LLMs to automate data cleaning, enrichment, and categorization tasks. • Knowledge of search system optimization and experience building or enhancing relevance and ranking algorithms. • Familiarity with taxonomy design, knowledge graph construction, or other advanced data modeling techniques to structure and enrich the catalog. • Experience with web scraping and data aggregation from diverse external sources to support catalog growth and data coverage.

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