Build ML Pipelines and deploy models Define and develop APIs and MCP Serverd Working on projects leveraging your expertise in data science, artificial-intelligence and machine learning Assist in breaking down complex business problems, developing solutions, and delivering with a high degree of focus on client satisfaction. Conduct market research, develop a point-of-view and communicate effectively back to clients and stakeholders. Bring innovative thinking, resourcefulness leveraging best practices and creativity to achieve successful client outcomes. Establish relationships with our clients at the appropriate levels, gain an understanding of the project work and problems encountered. Work with data sets of varying degrees of size and complexity including both structured and unstructured data. Piping and processing massive data-streams in distributed computing environments. Implement batch and real-time model scoring. Assemble large, complex data sets that meet functional / non-functional business requirements.



Apply business knowledge to analyze data, develop reports and solve problems *Perform ad hoc analyses of data depending on business needs. Participate in the analysis and resolution of issues related to information flow and content with data stakeholders. Technical skills required 5 + Years as an ML Ops Engineer with experience in the following: Proficiency in AWS SageMaker and AWS Cloud Services Experience with ML lifecycle tools (e.g., MLflow, Kubeflow) Familiarity with Weights & Biases for experiment tracking Hands-on with Databricks for scalable data and ML workflows Experience in Developing GitHub Actions using Typescript for CICD Understanding of Edge ML deployment strategies Skills in data preparation and feature engineering Soft skills required Communication, Agile Thinking, Adaptability, problem-solving, work ethic LI-LATAM

📌 Ml Ops Engineer (Guadalajara)
🏢 Ntt Data
📍 Guadalajara