This role is eligible for our hybrid work model: Two days in-office. Based in our Mumbai office.

Platform Engineer (MLOps & DataOps)
The MLOps & Data DevOps team enables Priceline’s data engineering, machine learning, and GenAI teams through secure, scalable, reliable, and governed platforms.
We build and operate the infrastructure, automation, deployment pipelines, observability, and self-service capabilities that allow engineering teams to deliver data and ML workloads safely to production.
If you enjoy working at the intersection of cloud infrastructure, DevOps, SRE, data platforms, and machine learning operations, this role offers an prospect to build platform capabilities used across Priceline.

Why this job’s a big deal
As Priceline expands its use of data, real-time analytics, machine learning, and GenAI, reliable platform engineering is critical to delivering business value safely and efficiently.
You will help operate the platform foundation behind data pipelines, ML pipelines, model endpoints, and LLM workloads. Your work will improve deployment speed,



platform reliability, cost visibility, security, and the self-service experience for data and ML engineering teams.
This role is focused on platform engineering and operations. Data and ML teams own business logic, model development, testing, and domain-level data quality; the MLOps & DataOps team owns the infrastructure, deployment paths, automation, governance, and reliability practices that enable those workloads.

In this role, you will:
1. Cloud Platform Infrastructure & Automation
• Build, maintain, and improve Terraform modules and configurations for GCP data and ML platform services.
• Provision, operate, and automate cloud data and ML platform services such as Cloud Composer/Airflow, Dataproc, Dataflow, BigQuery, Cloud Storage, and Vertex AI.
• Support platform upgrades, configuration changes, capacity planning, and operational improvements across development, QA, and production environments.
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📌 Platform Engineer (Mumbai)
🏢 Priceline
📍 Mumbai