MLOps Engineer – ML Platform Engineer

This is a fully remote position, open to applicants in Mexico.

📋 Description

• Oversee the performance, latency, errors, and availability of AI models and agents in production.

• Monitor changes in model drift, data distribution, and output stability.

• Track business KPIs associated with AI behavior.

• Identify and address production incidents related to AI performance or degradation.

• Implement rollbacks, throttling, or model deactivation when predetermined thresholds are exceeded.

• Assist in root-cause analysis and conduct post-incident reviews.

• Facilitate the deployment, versioning, and release of AI models and agents through CI/CD pipelines.

• Manage registries and metadata that encompass model ownership, lineage, risk classification, and approvals.

• Ensure the safe promotion of models and agents across development, testing, and production environments.

• Guarantee that AI systems comply with Responsible AI principles, internal controls, and audit requirements.

• Maintain audit trails, logs, and approval documents for risk, compliance, and regulatory purposes.

• Promote fairness, bias mitigation, explainability, and transparency monitoring in production.

• Integrate AI systems with monitoring, logging, and alerting frameworks.

• Work with cloud infrastructure, including containers, event streaming, and APIs.

• Collaborate with product, engineering, and data teams to standardize AI Ops patterns and blueprints.

⛳️ Requirements

• Proficient in Python with experience supporting machine learning or large language model-based systems.

• Knowledgeable in Model Ops / MLOps, particularly during the operational phase post-deployment.

• Familiarity with monitoring and logging systems.

• Experience with CI/CD pipelines.

• Background in containerized deployments, such as Docker-based environments.

• Understanding of cloud platforms, with a preference for Azure.

• Experience in troubleshooting production issues.

• Capability to work collaboratively across product, data science, engineering, and risk teams.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Opportunities for professional development and continuous learning.

• Flexible working hours and remote work options.

• Comprehensive health benefits and wellness programs.

• Supportive and inclusive company culture.