Machine Learning Engineer | Contract | Remote, MX

techholding; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Techholding is seeking a senior ML engineer to develop NLP and LLM capabilities for a risk intelligence platform, turning large volumes of online text into actionable signals.

Based remotely in Mexico, you will work as an individual contributor delivering production ML models, with regular collaboration with U.S.-based engineering and product stakeholders.

Responsibilities include deploying scalable services, monitoring model performance, and improving data pipelines for multilingual sources.

Qualifications

• 4+ years building and deploying production ML models.
• Strong Python and ML framework experience.
• Experience with NLP tasks in real-world text.
• Experience with LLMs and retrieval-augmented generation.
• Experience deploying ML services on cloud with Docker and CI/CD.

Responsibilities

• Design, train, and deploy models for text classification and extraction.
• Develop LLM features via prompt design and RAG workflows.
• Build embedding pipelines and semantic search to surface threats.
• Deploy scalable ML services with monitoring and cost goals.
• Create evaluation data to track bias, errors, and drift.
• Improve ingestion and labeling pipelines for multilingual text.
• Monitor production models and retrain as needed.
• Join daily standups with the U.S.-based team.

Skills

Python

NLP

LLMs

Prompt engineering

Vector search

Model deployment

CI/CD

Tools

PyTorch

TensorFlow

Hugging Face Transformers

Docker

FAISS

Job description

Role overview

Develop machine learning capabilities for a risk intelligence platform that helps organizations identify and assess online threats, including disinformation, reputational attacks, and security concerns. Based remotely in Mexico, you’ll work as an individual contributor building NLP and LLM systems that turn large volumes of online text into useful signals, collaborating regularly with U.S.-based engineering and product stakeholders.

Responsibilities

• Design, train, and deploy models for text classification, entity extraction, clustering, and topic or narrative detection.
• Develop LLM features using prompt design, retrieval-augmented generation, and agent workflows.
• Build embedding and semantic search pipelines to connect related content and surface potential threats.
• Deploy models as scalable, monitored services with defined accuracy, latency, and cost goals.
• Create evaluation data and methods to track quality, bias, errors, and model drift.
• Improve ingestion, labeling, and feature pipelines for large, noisy, multilingual text sources.
• Monitor production models, investigate quality problems, and retrain when needed.
• Join daily standups and technical discussions with the U.S.-based team.

Requirements

• At least four years of professional experience building and deploying production machine learning models.
• Strong Python skills and practical experience with PyTorch, TensorFlow, or Hugging Face Transformers.
• Applied NLP experience with real-world text, such as classification, named entity recognition, topic modeling, or semantic similarity.
• Hands-on experience with LLMs, prompt engineering, and retrieval-augmented generation.
• Experience with embeddings and vector search.
• Experience deploying and operating ML services on a major cloud platform, with Docker and CI/CD.
• Knowledge of model evaluation, including metrics, test sets, error analysis, and production monitoring.

Nice to have

• Background in trust and safety, threat intelligence, disinformation research, or social media data.
• Agentic AI experience, multilingual NLP— especially Spanish text—or familiarity with MLOps and large-scale data processing.
• Experience working with U.S.-based clients or distributed teams.

Benefits and work setup

Remote contract role based in Mexico, with daily collaboration across locations.