1 per engagement
Agentic AI
Applied ML Engineer
Seniority band: 6–10 years1 per engagement
Works where retrieval meets messy real data — embeddings, chunking strategy and ranking tuned against what users actually search for.
What this role owns
- Retrieval quality: embeddings, chunking, reranking and the metrics that prove it
- Index freshness and the pipeline that keeps it current
- Search and recommendation relevance against real query logs
- Data cleaning where the corpus quality caps the whole system
Tooling and capability
Agentic AI
RAG pipelinesEmbeddings & rerankingVector searchChunking strategy
Software
PythonPyTorchFastAPIPostgreSQL + pgvectorSpark
Platform
AWS SageMakerPineconeQdrantDocker
