MLOps Engineer - 2714

Xideral; Región Centro; Presencial; MXN 719,000 - 1,079,000; Jornada completa

Descripción de la vacante

A leading tech company is seeking an experienced MLOps Engineer to design, deploy, and maintain scalable ML solutions in a hybrid work environment. The ideal candidate will possess a strong background in MLOps and AWS, particularly with SageMaker. Responsibilities include building ML pipelines, defining APIs, and collaborating with cross-functional teams. The role requires advanced programming skills and the ability to work in both remote and on-site settings. This position offers a dynamic work schedule from Monday to Friday, focusing on innovation and continuous improvement.

Formación

• 5+ years of experience as an MLOps Engineer.
• Advanced proficiency in Python programming.
• Experience developing CI/CD pipelines using GitHub Actions (TypeScript).
• Familiarity with ML training and inference workflows.

Responsabilidades

• Build, deploy, and maintain ML pipelines and production-ready models.
• Define and develop APIs and MCP servers to support ML solutions.
• Implement batch and real-time model scoring in distributed environments.
• Establish strong relationships with clients and internal teams.

Conocimientos

MLOps

AWS

CI/CD automation

Container orchestration

Python programming

Data science and machine learning

Communication skills

Educación

Bachelor’s degree or higher in Computer Science, Engineering, Data Science, or related field

Herramientas

AWS SageMaker

MLflow

Kubeflow

Databricks

GitHub Actions

Kubernetes

Descripción del empleo

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