ML Engineer (Recommendation Systems)

Requisitos

• ~4+ years of production ML experience in recommendations, search, or ranking, with full-cycle involvement from model training to producti..
• Experience building modern RecSys models and launching them to production with measurable impact on product and business metrics
• A/B tests: designed, launched, and analyzed them (not only read results)
• Autonomy: can design a system from idea to production without daily supervision
• Python (production-grade code)

Desejáveis

• Multimodal embeddings (CLIP/SigLIP-like), content-based product representations
• Vector databases: Qdrant, Milvus, Pinecone
• Feature stores: Feast, Tecton
• MLOps: MLflow, experiment tracking, model registry
• Causal inference, uplift, interleaving