Machine Learning Engineer | Contract | Remote, MX

Tech Holding; Región Centro; Remote; MXN 1,200,000 - 2,000,000; Part time

Job summary

Tech Holding is seeking a hands‑on Machine Learning Engineer in Mexico to join a team building an AI‑powered risk intelligence platform. You'll design, train, and deploy NLP and LLM‑based models, processing large multilingual text data and surfacing emerging threats, while collaborating with US‑based engineers and stakeholders.

The role emphasizes end‑to‑end model development, deployment, monitoring, and ongoing improvement, with a contract arrangement and remote work from Mexico.

Qualifications

• 4+ years of professional experience building and deploying machine learning models in production.
• Strong Python skills and hands‑on experience with PyTorch, TensorFlow, or Hugging Face Transformers.
• Practical NLP experience, such as classification, named entity recognition (NER), topic modeling, or semantic similarity on real‑world text data.
• Hands‑on experience building with LLMs (OpenAI, Anthropic, or open‑source models), including prompt engineering and RAG.
• Experience with embeddings and vector search (e.g., pgvector, Pinecone, OpenSearch, or FAISS).
• Experience deploying and operating ML services on AWS, GCP, or Azure, using Docker and CI/CD.
• Solid grasp of model evaluation, including metrics, test sets, error analysis, and production monitoring.

Responsibilities

• Design, train, and deploy ML models for text classification, entity extraction, clustering, and narrative and topic detection.
• Build and improve LLM‑powered features, including prompt design, retrieval‑augmented generation (RAG), and agentic workflows.
• Develop embedding and semantic‑search pipelines to group related content and surface emerging threats.
• Productionize models as scalable, monitored services with clear latency, cost, and accuracy targets.
• Build evaluation frameworks and datasets to measure model quality, bias, and drift over time.
• Work with data engineering to improve ingestion, labeling, and feature pipelines for high‑volume, noisy, multilingual text data.
• Monitor and retrain models in production, and debug quality issues end to end.
• Join daily standups and technical discussions with the US‑based client team.

Skills

Python

PyTorch

TensorFlow

HuggingFace Transformers

NLP

NER

Topic Modeling

Semantic Similarity

LLMs

Prompt Engineering

RAG

Embeddings

Vector Search

AWS

GCP

Azure

Docker

CI/CD

Model Evaluation

Monitoring

Tools

pgvector

Pinecone

OpenSearch

FAISS

Docker

CI/CD

Job description

Mexico, Remote

About us:

Working at Tech Holding isn't just a job, it's an opportunity to be a part of something bigger. We are a full-service consulting firm that was founded on the premise of delivering predictable outcomes and high-quality solutions to our clients. Our founders and team members have industry experience and have held senior positions in a wide variety of companies – from emerging startups to large Fortune 50 firms – and we have taken our combined experiences and developed a unique approach that is supported by the principles of deep expertise, integrity, transparency, and dependability.

The Role:

We’re looking for a hands‑on Machine Learning Engineer in Mexico to join our team building an AI‑powered risk intelligence platform. The platform helps enterprises detect, assess, and respond to emerging online threats, including disinformation, reputational attacks, and security risks. You’ll design, build, and deploy NLP and LLM‑based models that process large volumes of data from mainstream and niche online sources. You’ll collaborate daily with US‑based engineers and product stakeholders as an individual contributor.

Key Responsibilities:

• Design, train, and deploy ML models for text classification, entity extraction, clustering, and narrative and topic detection
• Build and improve LLM‑powered features, including prompt design, retrieval‑augmented generation (RAG), and agentic workflows
• Develop embedding and semantic‑search pipelines to group related content and surface emerging threats
• Productionize models as scalable, monitored services with clear latency, cost, and accuracy targets
• Build evaluation frameworks and datasets to measure model quality, bias, and drift over time
• Work with data engineering to improve ingestion, labeling, and feature pipelines for high‑volume, noisy, multilingual text data
• Monitor and retrain models in production, and debug quality issues end to end
• Join daily standups and technical discussions with the US‑based client team

Requirements:

• 4+ years of professional experience building and deploying machine learning models in production
• Strong Python skills and hands‑on experience with PyTorch, TensorFlow, or Hugging Face Transformers
• Practical NLP experience, such as classification, named entity recognition (NER), topic modeling, or semantic similarity on real‑world text data
• Hands‑on experience building with LLMs (OpenAI, Anthropic, or open‑source models), including prompt engineering and RAG
• Experience with embeddings and vector search (e.g., pgvector, Pinecone, OpenSearch, or FAISS)
• Experience deploying and operating ML services on AWS, GCP, or Azure, using Docker and CI/CD
• Solid grasp of model evaluation, including metrics, test sets, error analysis, and production monitoring

Nice to have:

• Experience with trust and safety, threat intelligence, disinformation research, or social media data
• Experience building agentic AI systems or tool‑using LLM workflows (e.g., LangChain, LlamaIndex, or custom frameworks)
• Multilingual NLP experience, especially Spanish‑language text
• Familiarity with MLOps tooling such as MLflow, SageMaker, Vertex AI, or Weights & Biases
• Experience with streaming or large‑scale data processing (e.g., Kafka, Spark, or Airflow)
• Previous experience working with US‑based clients or distributed teams

Location:

• Remote, Mexico

Time Zone:

• Must work overlapping hours with US Eastern Time

Employment type:

• Contract

Tech Holding is proud to be an Equal Opportunity Employer and is committed to fostering a diverse and inclusive workplace. We welcome applicants from all backgrounds and experiences, and we consider qualified applicants without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally protected characteristic. If you require accommodation in the application process, please contact our HR