SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Tabby is a fintech platform that enables flexible payments and financial freedom for over 25 million users globally. The company operates a marketplace where users discover products, powered by a sophisticated ML-driven content pipeline.
You will lead the Content Quality & Personalisation team within Tabby Marketplace, which owns the data infrastructure that makes the marketplace work. The team manages a catalogue of 25M+ products ingested from thousands of merchants through feeds and e-commerce plugins (Shopify, Salla, Zid, Amazon, etc.), then enriches, categorises, translates, moderates and publishes this data largely through ML automation.
Your team comprises ML engineers, backend and frontend engineers, QA specialists, and a product analyst. You will oversee the LLM-based enrichment pipeline (categorisation, attribute extraction, translation), item representation models and embeddings powering search and recommendations, ML-assisted moderation replacing manual review, and the labeling and evaluation platform supporting all systems.
Key responsibilities include owning the end-to-end product data pipeline with clear SLAs for freshness, coverage and quality; leading the ML roadmap for catalogue intelligence including category trees, attribute coverage, translation quality, moderation and embeddings; driving large cross-team projects to production; contributing to quarterly planning and defining OKRs for catalogue quality; reviewing feature designs to ensure non-functional requirements (ML evaluation, inference cost, latency, data residency) are met; building and maintaining evaluation and labeling infrastructure; overseeing technical debt and incident handling; hiring and developing team members; fostering cross-functional collaboration with Shopping, Offers, Monetisation, catalogue operations and partner support; and establishing a results-oriented culture with transparent delivery and optimised processes.
You will work in a fast-growing fintech operating at scale: $18B+ annual transaction volume, 70,000+ global brand partners, $6.5B valuation, and $1B+ in funding. The technical stack includes Python, Go, PostgreSQL, Pub/Sub, BigQuery, GCS, Kubernetes, Google Cloud Platform, Airflow, and microservices architecture.
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
- 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 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
