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
#LI-Remote
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
