MLOps Engineer

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Our values drive everything: ONE IATA – collaboration across teams, TRUSTED – doing the right thing, INNOVATIVE – building tomorrow, INCLUSIVE – embracing diverse perspectives.

Employment Type: Permanent About the team you are joining Reporting to the Lead MLOps Engineering, the MLOps Engineer will develop and maintain solutions and infrastructure for AI projects across IATA, collaborating with Data Scientists, Cloud, and Data Engineers to transform proof‑of‑concept models into production‑ready solutions and provide operational support for IATA Data Scientists globally.

Great team player, operating with humility, integrity, accountability and a collaborative mindset. Why you will love working here At IATA, we represent over 350 airlines worldwide, striving to make aviation safer, smarter, more sustainable, and inclusive.

We prioritize diversity, equity, and inclusion, certified by the Equal Salary Foundation with equal pay and family‑friendly policies. We encourage community involvement, offer time off for volunteering, and support flexible work options, including remote, hybrid, and a generous "work from abroad" policy, plus a birthday off.

What your day would be like Deliver production‑ready ML systems end to end, from data pipelines to packaged, versioned, scalable, and deployed models. Implement and maintain CI/CD/CT pipelines for ML workflows, including automated testing, model/version management, packaging, deployment automation, and reliable delivery practices.

Monitor, maintain, and continuously improve ML systems in production, optimizing model performance, infrastructure cost, scalability, reliability and operational efficiency. Apply and promote strong ML engineering best practices, including data governance, security, reproducibility, standardized reusable patterns, and shared platform capabilities.

Provide operational and technical support to Data Scientists across IATA, including ticketing, monitoring, troubleshooting, and mentoring on Cloud, DevOps, AI system design and production ML best practices.

We would love to hear from you if Advanced degree in Computer Science, Engineering, or another science‑related field, or equivalent relevant experience. 5+ years of experience in MLOps Engineering, DevOps, Data Science, or a similar technical role with hands‑on exposure to production ML/AI systems.

Strong programming and data skills, including proficiency in Python and SQL. Solid DevOps and Cloud engineering expertise, including CI/CD, Terraform, Docker, automation, infrastructure‑as‑code, and deployment best practices; designing scalable Cloud solutions (ideally on AWS).

Strong AI knowledge, including ML/AI and data‑processing solutions, as well as a solid understanding of Generative AI/LLMs, traditional ML models, and ML workflows. Travel Required: No #J-18808-Ljbffr