Engineering Manager, ML

🔥 12 hours ago

🇪🇸 Spain – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

👮‍♀️ Software Engineering Manager

👻 Ghost score 11%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Tabby

WebsiteLinkedInAll Job Openings

201 - 500 employees

💳 Fintech

🛍️ eCommerce

💰 $58M Series C on 2023-01

Fintech • eCommerce

Tabby is a payment solutions company that allows shoppers to split their purchases into four interest-free monthly payments, making shopping more accessible and convenient. Tabby provides an app that helps users discover and track the best products, brands, and deals. The service is available for a wide range of categories, including fashion, beauty, electronics, and more, and integrates with VISA for broad acceptance. Additionally, Tabby offers business solutions to increase sales by removing price barriers and supports shoppers through its Tabby Care service, which facilitates easy returns and payment holds in case of purchase issues.

📋 Description

• Own the end-to-end product data pipeline: ingestion from feeds and plugins, ML enrichment, moderation and publication, with clear SLAs for freshness, coverage and quality • Lead the ML roadmap for catalogue intelligence, including category tree and attribute coverage, translation quality, ML-assisted moderation, item embeddings and recommendations • Lead large cross-team projects and drive them to production • Contribute to quarterly planning and roadmap definition; define and report OKRs for catalogue quality and personalisation • Review feature designs and ensure non-functional requirements are met, including ML evaluation, inference cost, latency and data residency • Build and maintain evaluation and labeling infrastructure to measure model changes before production • Oversee technical debt management and incident handling across ML and backend services • Hire, evaluate, and motivate team members; develop ML engineers into owners of business outcomes • Build cross-team collaboration with Shopping, Offers, Monetisation, catalogue operations and partner support • Foster a results- and business-oriented culture • Monitor key team performance indicators • Ensure process and delivery transparency for stakeholders and partner functions • Optimise processes to improve productivity • Lead a cross-functional team of ML engineers, backend and frontend engineers, QA and a product analyst • Work closely with Shopping, Offers and Monetisation teams, catalogue operations and partner support

🎯 Requirements

• 6+ years of engineering experience, including 3+ years building production ML systems (NLP, LLM applications, embeddings, or classification at scale) • 2+ years as an Engineering Manager or ML Team Lead at a fast-growing e-commerce, marketplace or fintech company • Hands-on experience shipping LLM-based products: prompt and pipeline design, fine-tuning, evaluation, cost and latency control, self-hosted and API-based models • Experience building and operating large-scale data and ML pipelines (batch and streaming), and making them observable, reproducible and reliable • Solid backend fundamentals; comfortable reviewing Go and Python services and reasoning about distributed systems • Strong grasp of ML evaluation: golden datasets, labeling workflows, offline metrics, and A/B testing tied to business outcomes • Product sense connecting catalogue quality to conversion, discovery and merchant growth • Proactive mindset and ability to work independently • Strong communication skills in English (B2 level or higher) • Nice to have: experience with product catalogues, PIM systems, or marketplace content moderation • Nice to have: experience with Arabic-language content • Nice to have: familiarity with data residency and regulated-data requirements

🏖️ Benefits

• Full-time B2B contract • Fully remote setup • Up to 20% tax allowance • 22 paid leave days annually • Stock options (ESOP) in a fast-scaling, pre-IPO company • Flexi benefits you can use for wellness, travel, or learning • Work alongside a high-performing, international engineering team in a global fintech unicorn