Platform Engineer

Posted 3 Days Ago
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Mumbai, Maharashtra, IND
Hybrid
Mid level
Travel
The Role
Build and operate secure, scalable MLOps and DataOps platforms on GCP. Responsibilities include Terraform-based infrastructure automation, CI/CD and GitOps pipelines, Kubernetes and ML platform operations, observability, incident response, security controls, governance, cost optimization, and self-service enablement for data and machine learning teams.
Summary Generated by Built In

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 opportunity 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.
  • Develop reusable automation and internal tools using Python and Shell scripting.
  • Apply infrastructure-as-code, change-management, security, and auditability standards to platform changes.

2. CI/CD, GitOps & Self-Service Enablement

  • 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.

3. MLOps & LLMOps Platform Operations

  • 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.

4. Monitoring, Observability, Security & SRE

  • 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.

5. Cost, Governance & Platform Enablement

  • 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.

Who you are:

  • Degree & Experience: B.Tech or B.E in Computer Science, Information technology, or equivalent practical experience, with 4–6 years of experience in DevOps, SRE, cloud platform engineering, MLOps, DataOps, or a closely related discipline.
  • Cloud Infrastructure: Strong hands-on experience with Google Cloud Platform or equivalent public cloud technologies. Experience with GCP services such as Cloud Composer, Dataproc, Dataflow, BigQuery, Google Cloud Storage, or Vertex AI is highly relevant.
  • Infrastructure as Code: Strong practical experience with Terraform for infrastructure provisioning, configuration management, reusable modules, and controlled production changes.
  • Containers & Kubernetes: Hands-on experience with Docker and Kubernetes. Experience with GKE is preferred for GCP environments.
  • CI/CD & GitOps: Experience building or operating CI/CD pipelines and Git-based deployment workflows using GitHub Actions, Argo CD, Codefresh, Jenkins, or equivalent tools.
  • Automation & Scripting: Proficiency in Python and Shell scripting for platform automation, operational tooling, pipeline hooks, and internal utilities.
  • Data & Workflow Platforms: Experience supporting Apache Airflow/Composer, Dataproc, Dataflow, Spark, BigQuery, or comparable data-processing and workflow-orchestration technologies.
  • MLOps: Experience supporting ML pipelines, model deployments, inference endpoints, model-serving infrastructure, or ML platform operations.
  • Reliability & Operations: Experience with monitoring, logging, alerting, incident response, on-call support, troubleshooting, and root-cause analysis for production systems.
  • Security & Governance: Working knowledge of IAM, RBAC, service accounts, secrets, vulnerability management, networking fundamentals, and secure cloud operations.
  • Operational Mindset: Strong ownership, structured problem-solving, documentation, communication, and collaboration skills.

 

Nice-to-Haves:

  • 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.

#LI-Hybrid


Who We Are

WE ARE PRICELINE.

Our success as one of the biggest players in online travel is all thanks to our incredible, dedicated team of talented employees. Priceliners are focused on being the best travel deal makers in the world, motivated by our passion to help everyone experience the moments that matter most in their lives. Whether it’s a dream vacation, your cousin’s graduation, or your best friend’s wedding - we make travel affordable and accessible to our customers. 

Our culture is unique and inspiring (that’s what our employees tell us). We’re a grown-up, startup. We deliver the excitement of a new venture, without the struggles and chaos that can come with a business that hasn’t stabilized.  

We’re on the cutting edge of innovative technologies. We keep the customer at the center of all that we do. Our ability to meet their needs relies on the strength of a workforce as diverse as the customers we serve. We bring together employees from all walks of life and we are proud to provide the kind of inclusive environment that stimulates innovation, creativity and collaboration.

Priceline is part of the Booking Holdings, Inc. (Nasdaq: BKNG) family of companies, a highly profitable global online travel company with a market capitalization of over $80 billion. Our sister companies include Booking.com, BookingGo, Agoda, Kayak and OpenTable. 

If you want to be part of something truly special, check us out! 

Flexible work at Priceline

Priceline is following a hybrid working model, which includes two days onsite as determined by you and your manager (ideally selecting among Tuesday, Wednesday, or Thursday). On the remaining days, you can choose to be remote or in the office.

Perks & Benefits at Priceline

Our benefits are designed to support your health, wellbeing, and life inside and outside of work. Eligible Priceliners have access to:

Health & wellness coverage including medical, dental, vision, and mental health resources

Generous time off including PTO, holidays, a company-wide Priceline Pause reset week, and paid volunteer days

Work/life support including the ability to work up to 4 weeks per year from anywhere, parental leave, dependent care and family support resources, Summer Fridays, and office perks like stocked kitchens and catered meals (varies by location)

Financial security programs such as retirement plans with company contributions, life and disability coverage, and tax-advantaged accounts

Signature travel perks including employee-only discounts on hotels and flights, VIP deals, and Big Deal Bucks credits

Additional perks & discounts like travel and partner discounts, tuition support, legal support, and pet benefits

A people-first culture with Employee Resource Groups (ERGs), social events, recognition programs, and service awards that help you connect, grow, and celebrate together

Specific benefits and programs vary by location.

Inclusion is a Big Deal!

To be the best travel dealmakers in the world, we believe our team should reflect the broad range of customers and communities we serve. We are committed to cultivating a culture where all employees have the freedom to bring their individual perspectives, life experiences, and passion to work.

Priceline is a proud equal opportunity employer. We embrace and celebrate the unique lenses through which our employees see the world. We’d love for you to join us and help shape what makes our team extraordinary.

Applying for this position

We're excited that you are interested in a career with us. For all current employees, please use the internal portal to find jobs and apply.

External candidates are required to have an account before applying. When you click Apply, returning candidates can log in, or new candidates can quickly create an account to save/view applications.

Skills Required

  • B.Tech or B.E. in Computer Science, Information Technology, or equivalent practical experience
  • 4-6 years of experience in DevOps, SRE, cloud platform engineering, MLOps, DataOps, or a related discipline
  • Hands-on experience with Google Cloud Platform or equivalent public cloud technologies
  • Strong practical experience with Terraform for infrastructure provisioning and reusable modules
  • Hands-on experience with Docker and Kubernetes
  • Experience building or operating CI/CD pipelines and Git-based deployment workflows
  • Proficiency in Python and Shell scripting
  • Experience supporting Airflow or Composer, Dataproc, Dataflow, Spark, BigQuery, or comparable data technologies
  • Experience supporting ML pipelines, model deployments, inference endpoints, or ML platform operations
  • Experience with monitoring, logging, alerting, incident response, on-call support, troubleshooting, and root-cause analysis
  • Working knowledge of IAM, RBAC, service accounts, secrets, vulnerability management, networking, and secure cloud operations
  • Strong ownership, structured problem-solving, documentation, communication, and collaboration skills
  • Experience operating LLM gateways or GenAI platforms such as LiteLLM or Tyk
  • Experience with ML or LLM observability and evaluation platforms such as Arize or LangSmith
  • Experience with GKE 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

Priceline Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Priceline and has not been reviewed or approved by Priceline.

  • Healthcare Strength — Healthcare coverage is positioned as comprehensive, including medical, dental, and vision offerings alongside an EAP. Fitness reimbursement is also described as part of the standard health-and-wellness set.
  • Leave & Time Off Breadth — Time away is framed as well-supported through paid time off, company holidays, and paid volunteer days. These elements collectively broaden the non-cash value of the package for many employees.
  • Fair & Transparent Compensation — Pay is characterized as fair-to-decent in parts of the organization, with certain technical roles described as competitive. Total rewards can feel more acceptable when benefits and travel-related perks are factored in.

Priceline Insights

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The Company
HQ: Norwalk, CT
1,339 Employees
Year Founded: 1998

What We Do

At Priceline, part of Booking Holdings, Inc. [NASDAQ: BKNG], we believe every trip is a big deal to our customers. Whether it’s a much-needed getaway, wedding, reunion, graduation, or rooting on a favorite team—those are the moments that nobody should miss out on. Our mission? Be the best travel dealmakers in the world. We provide our customers with smart and easy ways to access the very best deals available on hotel rooms, flights, rental cars, vacation packages and cruises, so they can be there for the moments that matter the most to them. We do that by welcoming people who are at the top of their game, who want to learn and grow with others and who take their work seriously (but not themselves). We’re building a diverse and uniquely talented team to make sure our customers can be there for all those {big deal} moments. Come join us!

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