MLOps Engineer

MLOps Engineer – Hybrid (3 days On-site) in Guadalajara We are looking for an experienced MLOps Engineer to join us, supporting the design, deployment, and operation of scalable Machine Learning solutions across cloud and distributed environments. This role focuses on building robust ML pipelines, deploying models into production, and enabling end-to-end ML lifecycle management while collaborating closely with data science, engineering, and business teams. The ideal candidate has strong hands‑on experience in MLOps, cloud platforms (AWS), CI/CD automation, and container orchestration, with a solid understanding of ML training, inference, and data engineering workflows. Key Responsibilities Build, deploy, and maintain ML pipelines and production‑ready machine learning models. Define and develop APIs and MCP servers to support ML solutions. Work on projects leveraging data science, artificial intelligence, and machine learning expertise. Process and manage large‑scale structured and unstructured datasets . Implement batch and real‑time model scoring in distributed computing environments. Pipe and process massive data streams for scalable ML workflows. Assemble large and complex datasets to meet business and technical requirements. Apply business knowledge to analyze data, generate insights, and solve complex problems. Perform ad‑hoc data analysis based on business needs. Participate in issue analysis and resolution related to data flow and content with stakeholders. Establish strong relationships with clients and internal teams, ensuring high client satisfaction. Promote best practices, innovation, and continuous improvement in MLOps processes. Technical Skills Required 5+ years of experience as an MLOps Engineer . Strong proficiency in AWS , especially SageMaker and related cloud services. Experience with ML lifecycle tools such as MLflow and Kubeflow . Hands‑on experience with Weights & Biases for experiment tracking. Practical experience using Databricks for scalable data and ML workflows. Advanced Python programming skills. Experience developing CI/CD pipelines using GitHub Actions (TypeScript) . Hands‑on experience with Kubernetes for container orchestration. Solid understanding of ML training and inference workflows . Experience in data preparation and feature engineering . Familiarity with Edge ML deployment strategies . Soft Skills Strong communication skills. Agile mindset and adaptability. Problem‑solving orientation. High level of commitment and work ethic. Leadership and collaboration skills. Qualifications Bachelor’s degree or higher in Computer Science, Engineering, Data Science, or related field. Ability to work independently and collaboratively in hybrid environments. Advanced English (required) for interaction with global teams. Location & Schedule Location: Hybrid – Guadalajara, Jalisco (Tlaquepaque / Zapopan area) On‑site: 2 or 3 days per week offices in Av. Mariano Otero 1249, Torre Atlántico, Piso 2, WTC Remote in Mexico City and Queretaro Schedule: Monday to Friday, 9:00 AM – 6:00 PM #J-18808-Ljbffr