Senior ML Ops Engineer

Job summary

KAYAK is seeking a Senior MLOps Engineer to design and implement machine learning infrastructure and production lifecycle. This hands-on role involves building scalable infrastructure, maintaining automated pipelines, and collaborating with Data Scientists and Operations teams to ensure reliable and performant ML models.

Qualifications

• Experience building and operating ML platforms in production environments
• Solid working knowledge of containerization and orchestration (Docker, Kubernetes), Linux internals, and model serving at scale
• Familiarity with ML lifecycle tooling, including orchestration frameworks, feature stores, model registries, and drift or performance monitoring
• Experience owning production systems
• Comfort writing production-quality code in Python or a comparable language
• Experience modernizing production infrastructure with attention to reliability, risk, and cost
• Ability to take ownership of technical outcomes and communicate clearly

Responsibilities

• Build and maintain ML infrastructure end-to-end
• Own model deployment and serving
• Develop core MLOps capabilities
• Operationalize infrastructure for the ML team
• Improve platform reliability and performance
• Empower Data Scientists through standardized, optimized workflows

Skills

Relocation