MLOps Engineer

• Develop and improve platform features that support ML and AI lifecycle management, including LLM operations
• Build and maintain CI/CD pipelines for ML, AI, and LLM workflows, training, deployment, and monitoring
• Support reliable, scalable, and secure production environments for ML, AI, and GenAI workloads
• Automate infrastructure and environment provisioning using infrastructure-as-code
• Operate and monitor ML, AI, and LLM services and related platform components
• Perform root cause analysis, troubleshooting, and bug fixing
• Support data platform users with ML, AI, data ingestion, and processing workloads
• Collaborate with the platform team on architecture, reliability, and optimization
• Contribute to other platform areas as needed, depending on priorities and skills

Qualifications

• Master's / Bachelor's in any engineering / Software / Information Technology / Similar engineering specialization
• 3+ years of experience in designing and building complex data or ML platforms
• Experience with MLOps practices and the ML model lifecycle in production
• Experience with CI/CD pipelines for ML and software delivery
• Experience with containers and orchestration, such as Docker and Kubernetes
• Experience with infrastructure as code, such as Terraform
• Experience with ML platforms and tooling such as MLflow, Databricks, Dataiku, or similar
• Preferably experience with workflow orchestration tools such as Kestra, Airflow, or similar
• Preferably experience with Azure OpenAI, Foundry, Cortex, or similar GenAI/LLM platforms
• Preferably experience deploying and managing LLM applications and vector databases
• Experience with cloud environments, particularly Microsoft Azure
• Experience with data warehousing, data processing, or streaming technologies
• Strong experience in root cause analysis, troubleshooting, and operational support
• Strong skills in SQL, Python, and/or other relevant programming languages
• Preferably experience with distributed compute frameworks such as Apache Spark