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Tabby is a fintech platform that enables flexible payments and financial control for 25M+ users across the GCC region and beyond. The company has raised $1B+ in funding and is valued at $6.5B.
You will lead the Content Quality & Personalisation team within Tabby Marketplace, which owns the data infrastructure powering product discovery. The team manages a catalogue of 25M+ products from thousands of merchants, ingested through feeds and e-commerce plugins (Shopify, Salla, Zid, Amazon, etc.), then categorised, enriched, translated, moderated and published—largely through ML.
Your team comprises ML engineers, backend and frontend engineers, QA, and a product analyst. You will oversee the LLM-based enrichment pipeline (categorisation, attribute extraction, translation), item representation models and embeddings for search and recommendations, ML-assisted moderation replacing manual review, and the labeling and evaluation platform supporting all of it.
Key responsibilities include:
- Own the end-to-end product data pipeline: ingestion, ML enrichment, moderation, and publication with clear SLAs for freshness, coverage, and quality
- Lead the ML roadmap for catalogue intelligence: category trees, attribute coverage, translation quality, ML-assisted moderation, embeddings, and recommendations
- Lead large cross-team projects to production
- Contribute to quarterly planning and define/report OKRs for catalogue quality and personalisation
- Review feature designs and ensure non-functional requirements (ML evaluation, inference cost, latency, data residency) are met
- Build and maintain evaluation and labeling infrastructure for pre-production model validation
- Oversee technical debt and incident handling across ML and backend services
- Hire, evaluate, and develop team members; grow ML engineers into business-outcome owners
- Foster cross-team collaboration with Shopping, Offers, Monetisation, catalogue operations, and partner support
- Build a results- and business-oriented culture
- Monitor team performance indicators and ensure delivery transparency
- Optimise processes to improve productivity
You will work closely with Shopping, Offers, 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), making them observable, reproducible, and reliable
- Solid backend fundamentals; comfortable reviewing Go and Python services and reasoning about distributed systems
- Proficiency with the stack: Python, Go, PostgreSQL, Pub/Sub, BigQuery, GCS, Kubernetes, Google Cloud Platform, Airflow, and microservices architecture
- Strong grasp of ML evaluation: golden datasets, labeling workflows, offline metrics, and A/B testing tied to business outcomes
- Product sense: ability to connect catalogue quality to conversion, discovery, and merchant growth; strong prioritisation skills
- Proactive mindset and ability to work independently
- Strong English communication skills (B2 level or higher)
NICE TO HAVE:
- Experience with product catalogues, PIM systems, or marketplace content moderation
- Experience with Arabic-language content
- Familiarity with data residency and regulated-data requirements
