MLOps Engineer 2714

Xideral

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profile Job Location:

Guadalajara - Mexico

profile Monthly Salary: Not Disclosed
Posted on: Yesterday
Vacancies: 1 Vacancy

Job Summary

MLOps Engineer Remote in Mexico - 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.

We are looking for MLOps Engineers who can take models built by data scientists and ML engineers and create ML pipelines including training inference and endpoint workflows to deploy the models to production.

Key Responsibilities

  • Build deploy and maintain ML pipelines in production-ready machine learning models.

  • Pipe and process massive data streams for scalable ML workflows.
  • Define and develop APIs and MCP servers to support ML solutions.

  • Work in collaboration with Data Scientists Data Engineers and ML Engineers to coordinate pipelines maintenance and training in production.

  • Process and manage large-scale structured and unstructured datasets.

  • Implement batch and real-time model scoring in distributed computing environments.

  • 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 Engineerwith experience developing CI/CD pipelines in Production

  • 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.

  • 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

  • Bachelors 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: Remote Guadalajara Jalisco (Tlaquepaque / Zapopan area)

  • Address Office:Av. Mariano Otero 1249 Torre Atlántico Piso 2 WTC

  • Remote in: Guadalajara Michoacán Guanajuato San Luis Potosí Colima Mexico City and Querétaro
  • Schedule: Monday to Friday 9:00 AM 6:00 PM

Benefits:

  • Attractive Salary Premium Benefits
  • Performance bonuses grocery coupons and savings are found.
  • Aguinaldo premium vacations and vacations paid
  • SGMM Medical insurance family and Life insurance.

Candidates must include their compensation expectations in their applications and resumes in English. Apply now through this link:


Required Experience:

IC

MLOps Engineer Remote in Mexico - GuadalajaraWe 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 model...
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