Machine Learning Engineer | Contract | Remote, MX (Ciudad de México)

Machine Learning Engineer | Contract | Remote, MX (Ciudad de México)

18 oct
|
Tech Holding
|
Ciudad de México

18 oct

Tech Holding

Ciudad de México

Remoto: Teletrabajo

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 detectionBuild and improve LLM-powered features, including prompt design, retrieval-augmented generation (RAG), and agentic workflowsDevelop embedding and semantic-search pipelines to group related content and surface emerging threatsProductionize models as scalable, monitored services with clear latency, cost, and accuracy targetsBuild evaluation frameworks and datasets to measure model quality, bias, and drift over timeWork with data engineering to improve ingestion, labeling, and feature pipelines for high-volume, noisy, multilingual text dataMonitor and retrain models in production,



and debug quality issues end to endJoin daily standups and technical discussions with the US-based client teamRequirements:4+ years of professional experience building and deploying machine learning models in productionStrong Python skills and hands-on experience with PyTorch, TensorFlow, or Hugging Face TransformersPractical NLP experience, such as classification, named entity recognition (NER), topic modeling, or semantic similarity on real-world text dataHands-on experience building with LLMs (OpenAI, Anthropic, or open-source models), including prompt engineering and RAGExperience 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/CDSolid grasp of model evaluation, including metrics, test sets, error analysis, and production monitoringNice to have:Experience with trust and safety, threat intelligence, disinformation research, or social media dataExperience building agentic AI systems or tool-using LLM workflows (e.g., LangChain, LlamaIndex, or custom frameworks)Multilingual NLP experience, especially Spanish-language textFamiliarity with MLOps tooling such as MLflow, SageMaker, Vertex AI, or Weights & BiasesExperience with streaming or large-scale data processing (e.g., Kafka, Spark, or Airflow)Previous experience working with US-based clients or distributed teamsLocation:Remote, MexicoEmployment type:Contract#LI-RemoteTech 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

📌 Machine Learning Engineer | Contract | Remote, MX (Ciudad de México)
🏢 Tech Holding
📍 Ciudad de México

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