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
• 2. 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
• 3. MLOps (Must‑Have)
• What to look for:
• Model deployment (SageMaker, ECS, Fargate)
• Monitoring, logging, drift detection
• CI/CD for ML
• Feature store concepts

• 4. AWS Cloud Experience (Must‑Have
• )What to look for
• :S
• 3Glu
• eLambd
• aECS/Fargat
• eSageMake
• rIAM fundamental

• s
• 5. 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
• 7. LLM / Agentic Experience (Nice‑to‑Ha
• ve)What to look f
• or:Vector databa
• sesRAG pipeli
• nesLangChain / LlamaIn
• dexEmbedding generat
• ionBedrock / OpenAI A

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