Responsabilidades
As a LLM/Machine Learning Engineer the company expects you to perform the following tasks:
- Build LLM-powered features: retrieval (RAG), prompt/tool orchestration, evaluation harnesses.
- Own data pipelines and model lifecycle (training/fine-tuning/lightweight adapters, monitoring, rollback).
- Collaborate with product/eng to ship secure, reliable AI features (guardrails, PII controls).
- Track latency/cost/quality trade-offs; instrument experiments and A/Bs.
Requisitos
✨You are the person they are looking for if you have:
- 3–5+ yrs in ML/ML-Ops; recent LLM experience (OpenAI/Anthropic, open-source models).
- Python stack (Pydantic/FastAPI), vector DBs (PGVector/FAISS/Weaviate), embeddings & RAG patterns.
- AWS data/serving (S3, Lambda/ECS, Step Functions/SageMaker optional), CI/CD, observability.
- Strong English communication.
💜They will be more enthusiastic about you if you also have:
- Documented AI, function/tool calling, multi-turn agents, cost controls, safety evaluation.
- Fintech or risk modeling exposure.