Remote MLOps Engineer (SRE)

Description:

• A leading company in Mexico specializing in accounting software is looking for a highly skilled MLOps Engineer (SRE) to join the team.
• The role involves designing and operating observability solutions for ML models in production, including monitoring, alerts, and traceability.
• Responsibilities include developing dashboards and metrics to evaluate model performance, cost, and stability, as well as implementing structured logging, drift monitoring, data quality, and inference error tools.
• The MLOps Engineer will collaborate with data science and product teams to detect and mitigate incidents related to models in production.
• The position requires applying SRE practices such as chaos engineering, stress testing, staging testing, and continuous integration.

Requirements:

• Candidates must have 4+ years of experience as an SRE, DevOps, or Platform Engineer with ML projects.
• Fluency in technical English is required.
• Experience with orchestrators such as Airflow, Kubeflow, or experiment tracking tools (MLflow, Weights & Biases) is necessary.
• Experience in high-transaction environments such as banking, accounting, payroll, or logistics is a nice to have.
• Knowledge of model monitoring frameworks such as Evidently, Arize AI, WhyLabs, or similar is essential.
• Proficiency in Prometheus, Grafana, ELK/EFK, OpenTelemetry, or Datadog is required.
• Candidates must be proficient in Kubernetes, Docker, Helm, and infrastructure automation tools (Terraform, Pulumi).
• Solid fundamentals in CI/CD for ML pipelines, including testing, validation, and rollback, are necessary.

Benefits:

• The job offers an opportunity to work with a leading company in the accounting software industry.
• Employees will have the chance to collaborate with talented data science and product teams.
• The position provides a platform to apply and enhance SRE practices in a dynamic environment.
• The role allows for professional growth in the field of MLOps and machine learning engineering.