ML Engineer

Priceline; Mumbai; Hybrid; INR 4,500,000 - 6,500,000; Full time

Benefits offered by this job

Health & wellness coverage

Generous time off

Work/life support (remote weeks)

Financial security programs

Signature travel perks

A people-first culture

Job summary

Priceline is seeking a seasoned cloud-native software engineer to scale AI/ML platforms in a hybrid role. You will build AI-powered platform frameworks and tooling deployed to GKE clusters with GitOps workflows using ArgoCD and Codefresh, and enhance GenAI usage with standardized templates and reusable tooling.

You will develop AI/ML pipelines with Vertex AI and related services, collaborate with security teams on tooling integration, and implement LLMOps patterns for secure, scalable

Qualifications

• Bachelor’s Degree in Computer Science or equivalent experience.
• 4–6 years of cloud-native software engineering experience.
• Strong experience with GCP or another major cloud provider (Azure/AWS).
• Hands-on expertise with Kubernetes, Vertex AI, Docker and deployment workflows.
• High proficiency in Python for developing AI-powered apps.
• Experience with LLMOps toolchains (RAG, prompts, version management).
• Experience deploying apps via GitOps (ArgoCD or similar).
• Proven ability to support AI/ML models in production (monitoring, pipelines, retraining loops).
• Eagerness to learn and collaborate in a team; strong ethics and integrity.

Responsibilities

• Build AI-powered platform frameworks and tooling deployed to GKE clusters with GitOps workflows.
• Improve GenAI usage by providing templates, self-serve workflows, and reusable tooling.
• Develop guardrails, observability, and cost-optimized AI deployments.
• Build and maintain AI/ML pipelines using Composer, Vertex AI, Dataproc, Dataflow.
• Collaborate with security and infra teams to integrate enterprise tooling.
• Implement and standardize LLMOps patterns for governed model access.

Skills

Cloud-native software engineering

GCP (Vertex AI)

Kubernetes

Python

LLMOps toolchains

GitOps (ArgoCD)

AI/GenAI workloads

Education

Bachelor’s Degree in Computer Science

Tools

Kubernetes

Vertex AI

Docker

ArgoCD

GitHub Actions

Codefresh

Job description

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

Why This Job’s a Big Deal

As Priceline scales personalization, AI-driven optimization, and intelligent automation, a modern platform for data and AI/ML is mission-critical. You’ll help build the foundational systems that enable self‑service AI‑powered software engineering, data engineering, MLOps/LLMOps, and GenAI workloads, while democratizing access to trusted data and models. Your work will directly accelerate innovation across every product and business team at Priceline.

In This Role You Will Get To

Build AI‑Powered Platform Frameworks and Tooling

• Build AI‑powered Python apps and internal platform tooling deployed to GKE K8s clusters with GitOps‑based deployment workflows with GitHub Actions, ArgoCD and Codefresh. Leverage Istio gateways and service mesh patterns for traffic management.
• Improve developer productivity around GenAI usage by providing standardized templates, self‑serve workflows, and reusable tooling around AI/ML workloads. This includes tooling built using popular GenAI frameworks such as LangChain, LangGraph, etc. as well as retrieval‑augmented generation (RAG) and agent‑based application patterns.
• Collaborate on building guardrails and observability frameworks for LLMs—covering evaluation (evals), prompt management, safety, and cost optimization. Develop scalable evaluation pipelines for LLM‑based agents and integrate monitoring tools (e.g., Arize, LangSmith, LiteLLM). Contribute to frameworks enabling secure, policy‑aligned, and explainable AI deployments.

AI/ML Pipeline & Model Lifecycle

• Build, maintain, and troubleshoot AI/ML and GenAI pipelines, batch jobs, and custom workflows leveraging Composer (Airflow), Vertex AI, Dataproc, Dataflow etc. Support workflow orchestration for AI/ML workloads, spanning data preparation, evaluation, and deployment stages.
• Collaborate with centralized infrastructure platform teams and security teams to integrate enterprise security tooling such as NexusIQ, StackRox, and Wiz into AI/ML workflows.
• Implement and standardize LLMOps patterns using Gemini Enterprise, LiteLLM, or similar model gateways to enable governed model access.

Monitoring, Observability & Model Quality

• Use Arize (or similar tools) for model drift/quality monitoring, embeddings monitoring, and LLM evaluation patterns.
• Implement logging, alerting, and SLOs for ML workloads and pipelines with Splunk, New Relic, PagerDuty etc.
• Assist with incident response, root‑cause analysis, and long‑term platform improvements.

Who You Are

• Bachelor’s Degree in Computer Science or relevant experience.
• 4–6 years of experience in Cloud‑native software engineering.
• Strong experience with GCP (Vertex AI, GKE, Dataflow, Dataproc, Composer, BigQuery, etc.) or other major cloud providers (Azure/AWS).
• Hands‑on expertise with Kubernetes, Vertex AI, Docker and image‑based deployment workflows.
• High proficiency with Python or similar object‑oriented programming language, especially for developing AI‑powered apps.
• Experience with LLMOps toolchains (RAG pipelines, vector stores, prompt/version management, agent frameworks).
• Experience deploying apps via GitOps using ArgoCD or similar.
• Proven ability to support AI/ML models in production: monitoring, pipelines, debugging, retraining loops.
• Eagerness to learn new techniques, technologies, solve problems and contribute in a team environment.
• Illustrated history of living the values necessary to Priceline: Customer, Innovation, Team, Accountability and Trust.
• The Right Results, the Right Way is not just a motto at Priceline; it’s a way of life. Unquestionable integrity and ethics is essential.

Nice‑to‑Haves

• Familiarity with enterprise MLOps tooling and best practices.
• Good understanding of infosec and RBAC best practices, and security posture management.
• Exposure to SRE best practices and error budgets for AI/ML systems.

Perks & Benefits At Priceline

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

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.

Flexible work at Priceline

Priceline follows 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.