SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Tabby is a fintech platform reshaping how people shop, earn, and save. The company operates a marketplace of 25M+ products from thousands of merchants, serving over 70,000 global brands including Amazon, Noon, IKEA, and SHEIN. Tabby has raised over $1 billion in funding and is valued at $6.5 billion.
You will lead the Content Quality & Personalisation team within Tabby Marketplace, which owns the data infrastructure that powers product discovery. The team is responsible for a catalogue of 25M+ products ingested through feeds and e-commerce plugins (Shopify, Salla, Zid, Amazon, etc.), then categorized, enriched, translated, moderated, and published—largely through ML automation.
As Engineering Manager, you will lead a cross-functional team of ML engineers, backend and frontend engineers, QA, and a product analyst. The team operates:
- LLM-based enrichment pipelines (categorization, attribute extraction, translation)
- Item representation models and embeddings powering search and recommendations
- ML-assisted moderation replacing manual review
- Labeling and evaluation platforms
You will own the end-to-end product data pipeline with clear SLAs for freshness, coverage, and quality. You'll lead the ML roadmap for catalogue intelligence, including category trees, attribute coverage, translation quality, moderation, embeddings, and recommendations. You'll drive large cross-team projects to production, contribute to quarterly planning and OKRs, and review feature designs to ensure non-functional requirements (ML evaluation, inference cost, latency, data residency) are met.
You'll build and maintain evaluation and labeling infrastructure, oversee technical debt and incident handling, hire and develop team members, foster cross-team collaboration with Shopping, Offers, Monetisation, catalogue operations, and partner support, and establish a results-oriented culture.
The tech 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; ability to prioritize accordingly
- 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
