Consultant - Machine Learning Engineer

About the role

This role suits someone who is as comfortable in distributed systems and MLOps as in ML itself — think “software engineer who specializes in ML systems” rather than “data scientist who can code.” Design, build, and operate production ML pipelines: feature engineering, training pipelines, model serving, and monitoring — at Expedia's scale (millions of requests/day).

What you'll do

• Design, build, and operate production ML pipelines: feature engineering, training pipelines, model serving, and monitoring — at Expedia's scale (millions of requests/day)
• Build and maintain low-latency, high-availability model serving infrastructure (real-time inference for search/personalization; batch scoring for pricing/forecasting)
• Own CI/CD for ML: automated retraining, model versioning, shadow deployments, canary releases, and rollback strategies
• Build robust feature pipelines (batch and streaming) using Spark and Kafka, and maintain feature stores for training/serving consistency
• Collaborate with ML Specialists to productionize research prototypes — translating notebook code into tested, maintainable, scalable services

What you need

• 6–9 yrs of experience
• Machine learning
• MLOps
• Python
• Spark
• Kafka
• TensorFlow
• Any graduate

Good to have

• AWS
• Databricks
• Terraform
• Kubernetes
• Airflow
• CI/CD