AI Platform Engineer

Job summary

The AI Platform Engineer role focuses on operating, automating, and enhancing production AI services across media and localization sectors. Key responsibilities include building platforms for deploying and monitoring AI models, supporting model-serving environments, and implementing observability for AI services, utilizing technologies such as Kubernetes, Docker, and AWS services.

Qualifications

• Experience in MLOps, AI platform engineering, DevOps, software engineering, or production ML operations
• Experience deploying or operating AI/ML models, inference services, data services, or API-based production systems
• Strong scripting or programming skills using Python or similar languages
• Experience with containers, CI/CD, cloud environments, monitoring, and operational automation
• Understanding of model deployment concepts, model lifecycle management, versioning, validation, and rollback

Responsibilities

• Build and operate platforms for deploying, monitoring, and maintaining production AI models and services
• Support model-serving environments, inference pipelines, deployment workflows, and release automation
• Develop automation for model packaging, promotion, validation, rollout, rollback, and lifecycle management
• Implement monitoring, logging, alerting, and observability for AI services, including performance, latency, availability, error rates, and cost
• Partner with AI Engineers to move models, workflows, and AI services from prototype to production
• Partner with cloud platform, infrastructure, and application teams to ensure AI services run on secure, scalable, and reliable environments
• Help define operational standards for production AI systems, including runbooks, incident response, testing, and release readiness
• Support batch and real-time AI workloads where applicable
• Troubleshoot issues related to model serving, API behavior, environment configuration, infrastructure, and deployment pipelines
• Build reusable patterns for AI service deployment and integration across applications
• Contribute to evaluation and adoption of MLOps tools, model-serving frameworks, observability platforms, and AI infrastructure technologies

Skills

Relocation