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Priceline

Online travel agency offering discount deals

Platform Engineer (MLOps & DataOps)

Full-Time
No salary listed
Mid, Senior
Bachelor's
Mumbai, Maharashtra, India
HybridHybrid: two days in-office in Mumbai; remaining days may be remote or in-office.
DevOps & InfrastructurePlatform Engineering

About the job

Requirements
  • A B.Tech or B.E. in Computer Science or Information Technology, or equivalent practical experience, and 4–6 years of experience in DevOps, SRE, cloud platform engineering, MLOps, DataOps, or a closely related discipline.
  • Strong hands-on experience with Google Cloud Platform or equivalent public cloud technologies; experience with Cloud Composer, Dataproc, Dataflow, BigQuery, Google Cloud Storage, or Vertex AI is relevant.
  • Practical experience with Terraform for infrastructure provisioning, configuration management, reusable modules, and controlled production changes.
  • Hands-on experience with Docker and Kubernetes; GKE experience is preferred for GCP environments.
  • Experience building or operating CI/CD pipelines and Git-based deployment workflows using GitHub Actions, Argo CD, Codefresh, Jenkins, or equivalent tools.
  • Proficiency in Python and Shell scripting for platform automation, operational tooling, pipeline hooks, and internal utilities.
  • Experience supporting Apache Airflow/Composer, Dataproc, Dataflow, Spark, BigQuery, or comparable data-processing and workflow-orchestration technologies.
  • Experience supporting ML pipelines, model deployments, inference endpoints, model-serving infrastructure, or ML platform operations.
  • Experience with monitoring, logging, alerting, incident response, on-call support, troubleshooting, and root-cause analysis for production systems.
  • Working knowledge of IAM, RBAC, service accounts, secrets, vulnerability management, networking fundamentals, and secure cloud operations.
  • Experience operating LLM gateways or GenAI platforms such as LiteLLM, Tyk, or equivalent model-access layers.
  • Experience with ML/LLM observability and evaluation platforms such as Arize, LangSmith, or equivalent tools.
  • Experience with GKE platform operations, GPU workloads, vector databases, RAG infrastructure, or model-serving systems.
  • Experience implementing data, model, artifact, or pipeline lineage and reproducibility practices.
  • Experience with cloud cost optimization, capacity management, and FinOps for data and ML workloads.
  • Experience applying SRE, security, networking, or compliance practices to cloud data and ML platforms.
Responsibilities
  • 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.
  • Develop reusable automation and internal tools using Python and Shell scripting.
  • Apply infrastructure-as-code, change-management, security, and auditability standards to platform changes.
  • Build and operate governed CI/CD pipelines for Airflow DAGs, Dataproc jobs, BigQuery changes, ML pipelines, and model-serving infrastructure.
  • Implement reliable deployment, promotion, validation, rollback, and release processes using Git-based workflows.
  • Work with GitHub Actions, Argo CD, Codefresh, or equivalent CI/CD and GitOps tooling.
  • Create self-service patterns that allow data and ML teams to provision and deploy workloads safely without bypassing governance controls.
  • Improve developer experience, deployment reliability, and time to production through standardization and automation.
  • Support production ML workflows covering model training, pipeline execution, model deployment, endpoint operations, batch inference, and retraining.
  • Operate and improve ML platforms based on Vertex AI, Kubernetes/GKE, Docker, Kubeflow, or equivalent technologies.
  • Support model gateway and LLM platform capabilities such as LiteLLM, including model onboarding, access management, rate limiting, usage visibility, cost controls, and reliability improvements.
  • Help establish repeatable practices for model versioning, artifact management, model registries, feature stores, and data/model lineage.
  • Contribute to GenAI, RAG, model evaluation, guardrails, and AI observability capabilities.
  • Define and operate monitoring, logging, alerting, and reliability practices for data pipelines, ML pipelines, model endpoints, and platform services.
  • Establish meaningful SLIs/SLOs, escalation paths, runbooks, and error-management practices.
  • Use tools such as PagerDuty, Splunk, New Relic, Arize, or equivalent observability platforms.
  • Troubleshoot pipeline failures, deployment issues, infrastructure problems, endpoint failures, and performance degradation.
  • Participate in on-call support, contribute to root-cause analysis, and drive corrective and preventative actions.
  • Integrate IAM, RBAC, service-account controls, vulnerability scanning, secrets management, and compliance guardrails into platform workflows.
  • Improve cloud cost visibility, resource utilization, capacity management, and FinOps practices for data and ML workloads.
  • Evaluate, adopt, and operationalize platform capabilities that improve reliability, security, developer productivity, and operational efficiency.
  • Partner with Cloud Infrastructure, SRE, InfoSec, Data Engineering, Data Science, and ML teams to resolve platform and operational issues.
  • Document platform standards, operational procedures, troubleshooting guidance, and reusable deployment patterns.
Desired Qualifications
  • Experience operating LLM gateways or GenAI platforms such as LiteLLM, Tyk, or equivalent model-access layers.
  • Experience with ML/LLM observability and evaluation platforms such as Arize, LangSmith, or equivalent tools.
  • Experience with GKE platform operations, GPU workloads, vector databases, RAG infrastructure, or model-serving systems.
  • Experience implementing data, model, artifact, or pipeline lineage and reproducibility practices.
  • Experience with cloud cost optimization, capacity management, and FinOps for data and ML workloads.
  • Experience applying SRE, security, networking, or compliance practices to cloud data and ML platforms.

About the company

Priceline is an online travel marketplace that connects travelers with airlines, hotels, car rental companies, cruises, and vacation packages. It uses two business models: an agency model that earns commissions on bookings and a merchant model that buys travel services wholesale and resells them at a markup. It offers fixed-price listings and discount options such as Express Deals and Name Your Own Price, plus flexible options like free cancellations and pay-at-arrival, accessible via a mobile app. Under Booking Holdings, its goal is to help budget travelers access a wide range of options while giving consumers more negotiating power through transparent pricing and valuable deals.

Company Size

1,001-5,000

Company Stage

Series B

Total Funding

$77.4M

Headquarters

Norwalk, Connecticut

Founded

1998

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Simplify's Take

What believers are saying

  • Q2 2026 Booking Holdings revenue hit $7.35 billion, with room nights up 5%.
  • Penny users saved nearly ten minutes per trip and converted better in testing.
  • Booking Holdings raised 2026 transformation savings to $650 million, funding Priceline investment.

What critics are saying

  • FTC staff threatened a 2026 lawsuit over disclosures, fees, support, and billing.
  • Anthropic, Google Cloud, and OpenAI commoditize Penny's AI edge within months.
  • Expedia, Booking.com, and direct supplier apps squeeze Priceline's margins and traffic.

What makes Priceline unique

  • June 3, 2026 Penny turned Priceline into an agentic booking workflow.
  • Priceline owns inventory, payments, and preferences across 100-plus countries inside one conversation.
  • Booking Holdings gives Priceline scale, supplier leverage, and capital behind product iteration.

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Benefits

  • Hybrid Work Options
  • Remote Work Options

Growth & Insights and Company News

6 month growth

0%

1 year growth

0%

2 year growth

0%
PR Newswire
Jun 23rd, 2026
Americans cut alcohol, dining out to afford summer holidays despite rising costs

Priceline's 2026 State of Summer Travel Report reveals Americans are cutting back on nearly everything to fund summer holidays despite rising costs. The survey of 2,500 US adults found 79% plan to take at least one trip this summer, even though 44% say such a vacation feels out of reach. Eighty-four percent of Americans report paying more and getting less for travel, whilst 55% find it less affordable than last year. Over one-third have already cut everyday expenses to fund trips, with 83% of adults willing to give up alcohol before vacation. Parents and millennials face the most pressure, with 28% of millennials planning to spend $5,000 or more this summer. Sixty-nine percent regret past cost-cutting decisions, whilst half plan to use AI tools to find better deals.

PR Newswire
Jun 3rd, 2026
Priceline's Penny AI assistant goes fully agentic, booking trips in one conversation with Anthropic's Claude

Priceline has launched an enhanced version of Penny, its AI travel assistant, now powered by Anthropic's Claude. The agentic system allows travellers to move from trip planning to booking within a single conversation, handling complex requests like comparing flights across multiple destinations. The experience features an interactive map that updates during conversations, along with personalised recommendations called Penny's Pick and Penny's Take. Built on Priceline's proprietary AI stack, the system integrates Claude for conversational reasoning, whilst Google Cloud and OpenAI support search and voice capabilities. Penny connects to real-time inventory from thousands of partners across over 100 countries. Early testing shows travellers using Penny demonstrate higher conversion rates and save approximately ten minutes per trip compared to those calling customer support. The service now supports multiple languages.