MLOps Engineer, AI Platform

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September 2

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Omilia - Conversational Intelligence

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Artificial Intelligence • eCommerce • Customer Service

Omilia is a leader in Conversational AI, specializing in voice and chat solutions that enable natural, end-to-end customer interactions. Their Omilia Cloud Platform provides advanced AI-driven customer service tools, including real-time agent assistance, voice biometrics for fraud prevention, and data analytics to enhance customer insights. Serving industries such as finance, insurance, retail, automotive, and travel, Omilia focuses on automating customer service while ensuring a secure and personalized experience.

201 - 500 employees

Founded 2002

🤖 Artificial Intelligence

🛍️ eCommerce

📋 Description

• Hands-on technical leadership role to design and build an AI platform from the ground up. • Architect and build automated, scalable infrastructure powering Agentic AI, NLU, Voice Biometrics, and ASR for millions of users. • Make key technical decisions, establishing patterns, tools, and best practices for ML operations. • Collaborate with researchers, data scientists, ML engineers, and cloud architects to productize research. • Champion automation, governance, and performance across AI/ML initiatives. • Design and implement MLOps infrastructure on AWS using Terraform with focus on security, scalability, and cost-efficiency. • Build end-to-end CI/CD pipelines using GitLab and Jenkins for training, validation, deployments, and rollbacks. • Containerize ML models with Docker and deploy on Kubernetes using Helm; help architect and manage the Kubernetes platform. • Implement and manage observability stack (e.g., Prometheus and Grafana) to meet performance, reliability, and security SLAs.

🎯 Requirements

• 5+ years in a Senior DevOps, SRE, or MLOps role with a focus on production systems • Deep expertise in architecting and managing Kubernetes clusters in a production environment. • Proven mastery of at least one major IaC tool (Terraform is strongly preferred). • Strong proficiency in a systems-level scripting language (e.g., Python, Go). • A track record of building and maintaining CI/CD pipelines for critical production services. • Direct experience deploying and managing specific ML models (e.g., Agentic AI, NLU, ASR, TTS). • Experience with dedicated ML workflow orchestration tools (e.g., Kubeflow, Apache Airflow). • Familiarity with ML experiment tracking and model registry tools (e.g., MLflow, SageMaker Model Registry). • Experience deploying models on specialized hardware (e.g., GPUs, Inferentia, Trainium, etc.).

🏖️ Benefits

• Fixed compensation • Long-term employment with the working days vacation • Development in professional growth (courses, training, etc) • Being part of successful cutting-edge technology products that are making a global impact in the service industry • Proficient and fun-to-work-with colleagues • Apple gear.