Remote ML Engineer — NLP & Risk Intelligence Platform

Tech Holding; México; Remote; MXN 900,000 - 1,300,000; Full time

Job summary

Tech Holding is seeking a hands-on Machine Learning Engineer in Mexico to build an AI-powered risk intelligence platform. You will design, train, and deploy NLP/LLM models handling multilingual data and collaborating with US-based engineers and product stakeholders.

You’ll work on embedding pipelines, RAG workflows, and production services with performance targets, latency considerations, and robust monitoring. Remote work from Mexico supported.

Qualifications

• 4+ years of professional experience deploying ML models in production.
• Strong Python and hands-on PyTorch, TensorFlow, or Transformers experience.
• Practical NLP with classification, NER, or semantic similarity in real data.
• Hands-on LLM experience including prompt engineering and RAG.
• Experience with embeddings and vector search (PGVector, Pinecone, FAISS, OpenSearch).
• Experience deploying ML services on AWS, GCP, or Azure with Docker/CI/CD.

Responsibilities

• Design, train, and deploy ML models for text classification, NER, clustering.
• Develop LLM-powered features including prompt design and RAG.
• Build embedding and semantic-search pipelines to surface threats.
• Productionize models as scalable, monitored services with latency/ cost targets.
• Create evaluation datasets and monitoring for bias and drift.
• Collaborate with data engineering on ingestion, labeling, pipelines.
• Monitor and retrain models in production; debug end-to-end.
• Participate in daily standups with US-based client team.

Skills

Python

PyTorch

TensorFlow

Hugging Face Transformers

NLP

LLMs

RAG

Embeddings & vector search

AWS/GCP/Azure

Docker & CI/CD

Model evaluation & monitoring

Tools

Docker

CI/CD

MLflow

SageMaker

Job description

Tech Holding is seeking a hands-on Machine Learning Engineer in Mexico to build an AI-powered risk intelligence platform. You will design, train, and deploy NLP/LLM models handling multilingual data and collaborating with US-based engineers and product stakeholders.

You’ll work on embedding pipelines, RAG workflows, and production services with performance targets, latency considerations, and robust monitoring. Remote work from Mexico supported.