Data Engineer Lead / ML Engineer - 13+ Experience // Local to GA , NJ

Data Engineer / ML Engineer Someone who can build data + ML systems, not just pipelines or models. 50% Data Engineering + 30% ML Engineering + 20% MLOps Core Data Engineering (Must‑Have) What to look for: • Python (strong, hands‑on) • Spark / PySpark • Data modeling • Building scalable pipelines • Snowflake or similar cloud warehouse • Distributed systems experience 1. Machine Learning Engineering (Must‑Have) What to look for: • Feature engineering • Model‑ready datasets • Experience integrating ML models into pipelines • Understanding of ML workflows (training → evaluation → inference) • Experience with recommendation systems is a big plus 1. MLOps (Must‑Have) What to look for: • Model deployment (SageMaker, ECS, Fargate) • Monitoring, logging, drift detection • CI/CD for ML • Feature store concepts 1. AWS Cloud Experience (Must‑Have )What to look for • :S • 3Glu • eLambd • aECS/Fargat • eSageMake • rIAM fundamental s 1. Recommendation Systems (Strong Plu s)What to look fo • r:Nearest‑neighbor search (Faiss, Annoy, ScaN • N)Ranking mode • lsRetrieval + scoring pipelin • esEmbeddin gs6. Data + ML Integration (Must‑Hav e)What to look fo • r:End‑to‑end pipelines (data → features → model → inferenc • e)Batch + real‑time workflo • wsExperience with merchant, customer, or behavioral datasets is a pl us 1. LLM / Agentic Experience (Nice‑to‑Ha ve)What to look f • or:Vector databa • sesRAG pipeli • nesLangChain / LlamaIn • dexEmbedding generat • ionBedrock / OpenAI A PIs