IC3 – MLOps Engineer

Spin is FEMSA’s business unit that enriches and simplifies people's lives. It is an ecosystem of financial and digital solutions that creates added value by helping our users and communities make the most of their time and money. The Spin ecosystem consists of simple, agile, and accessible solutions that help our customers address everyday needs and receive rewards for doing so; such as the digital wallet, Spin by OXXO, the loyalty program, Spin Premia, and Spin Negocios, which offers various solutions for businesses, including NetPay and OXXO PAY.

Objective of the Role 

Responsible for operationalizing machine learning workflows by building scalable, reliable, and automated systems that bridge the gap between development and production environments. This role ensures that machine learning models are efficiently deployed, monitored, and maintained, while optimizing infrastructure to support seamless model performance and scalability in dynamic, real-world applications. 

Main Responsibilities 

• Deploy machine learning models into production environments in collaboration with data scientists and data engineers. 

• Develop and maintain automated pipelines for model training, testing, and deployment, ensuring reliability and efficiency. 

• Implement monitoring and alerting systems to track model performance and identify data drift, taking corrective actions as necessary. 

• Ensure the scalability, reliability, and reusability of machine learning models in production. 

• Manage the containerization and orchestration of machine learning workloads using tools such as Docker and Kubernetes. 

• Integrate machine learning workflows into existing CI/CD pipelines in partnership with DevOps teams. 

• Write unit and integration tests, document processes, and contribute to the engineering knowledge base. 

• Monitor and troubleshoot complex data and infrastructure issues to maintain operational excellence. 

• Collaborate with cross-functional teams to ensure alignment and smooth transitions of models from development to production. 

• Stay updated on emerging MLOps practices and technologies, contributing to the evolution of the organization’s capabilities. 

• Promote an autonomous work culture by encouraging self-management, accountability, and proactive problem-solving among team members. 

• Serve as a Spin Culture Ambassador to foster and maintain a positive, inclusive, and dynamic work environment that aligns with the company's values and culture. 

Must-have knowledge (Required)

• Proficiency in Python.

• Hands-on experience deploying and managing ML/AI models in production.

• Knowledge of Docker or Kubernetes.

• Experience with at least one cloud platform: GCP, AWS, or Azure.

• Basic understanding of data science and the role of a data scientist.

• Proven skills in designing, implementing, and maintaining automated training and deployment pipelines.

Required Knowledge and Experience 

• Minimum 3+ years of experience as an MLOps Engineer, Data Scientist, or Data Engineer, with a proven track record of deploying and managing ML/AI models in production. 

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or equivalent professional experience. 

• Relevant certifications in MLOps, DevOps, Data Engineering, or Cloud Platforms are a plus. 

• Proficiency in Python and at least one additional programming language (Java, Scala preferred). 

• Strong experience with containerization tools (Docker) and orchestration platforms (Kubernetes). 

• Expertise in cloud platforms (GCP, AWS, or Azure) and cloud-based data services. 

• Proficiency in designing, building, and maintaining data processing systems, including tools such as Apache Airflow, Lambda, or Glue. 

• Experience with SQL and NoSQL databases, including platforms like Snowflake, BigQuery, or Redshift. 

• Knowledge of DevOps practices, including CI/CD pipelines and version control systems (Git). 

• Familiarity with agile methodologies (e.g., Scrum, Kanban) and collaboration tools. 

• Strong scripting skills for automation and orchestration of workflows. 

• Solid understanding of monitoring and logging tools such as Prometheus, Grafana, or ELK Stack. 

• Strong problem-solving skills, with the ability to troubleshoot complex technical challenges. 

• Excellent written and verbal communication skills for collaborating with cross-functional teams and presenting findings effectively. 

• Detail-oriented mindset to ensure data accuracy and pipeline reliability. 

• Adaptability to thrive in a dynamic and fast-paced environment. 

Spin está comprometida con un lugar de trabajo diverso e inclusivo. 
Somos un empleador que ofrece igualdad de oportunidades y no discrimina por motivos de raza, origen nacional, género, identidad de género, orientación sexual, discapacidad, edad u otra condición legalmente protegida. 
Si desea solicitar una adaptación, notifique a su Reclutador.