ML Ops Engineer

Bengaluru, Karnataka, India

Zuora

Whether your business model is based on subscriptions, consumption, or a hybrid approach, our industry leading monetization solutions will help.

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Company Overview

At Zuora, we do Modern Business. We’re helping people subscribe to new ways of doing business that are better for people, companies, and ultimately the planet. This shift to the Subscription Economy puts customers first by building recurring relationships rather than one-time sales, enabling long-term sustainable growth. With our leading multi-product suite and deep expertise, we’re transforming industries and enabling the world’s most innovative companies to monetize new business models, deepen subscriber relationships, and optimize digital experiences.

The Team & Role

Are you excited to bring ML to life in production? Do you enjoy working at the intersection of scalable engineering and cutting-edge AI? Join Zuora Platform Tech and help shape the future of monetization.

As a Machine Learning Engineer in our 10X AI team (AI, ML, and Science), you'll design, implement, and maintain production-grade ML systems that power mission-critical business decisions and customer experiences. Your role will focus on building reliable pipelines, deploying models at scale, enabling experimentation, and creating the infrastructure that makes AI real across Zuora’s product suite.

Our Tech Stack

Core: Java, Spring, REST APIs, Microservices, Kafka, Spark, NodeJS, AWS, Kubernetes, Terraform, AngularJS
AI/ML: AWS Bedrock, SageMaker, Athena, Python, LangGraph, LangChain, Streamlit, Claude, Kubernetes
ML Infra: FAISS, Neo4j, MLFlow, Docker, CI/CD, Airflow, Vector DBs, Graph DBs

What You’ll Do

  1. Productionize ML Models – Deploy models (ML & GenAI) into robust production environments using modern ML infrastructure and MLOps practices.
  2. Optimize for Scale & Performance – Build scalable, low-latency ML services and APIs with observability, testing, and failover mechanisms.
  3. Pipeline Automation – Design and implement automated training, testing, and deployment pipelines using tools like SageMaker Pipelines, Airflow, and MLFlow.
  4. Model Monitoring & Maintenance – Implement monitoring for model drift, data quality, and performance metrics. Own retraining and rollback strategies.
  5. Partner with Scientists & Engineers – Collaborate with data scientists to take notebooks to production, and with software engineers to integrate ML into customer-facing systems.
  6. Champion Best Practices – Define best practices for ML development lifecycle, including CI/CD for models, reproducibility, and secure deployment.

Qualifications

  • 5+ years of experience in machine learning engineering or applied ML development
  • Proven experience deploying ML models to production, maintaining APIs, and building CI/CD pipelines for ML
  • Strong foundations in data engineering: ETL, batch/stream processing, and data quality practices
  • Hands-on experience with MLOps tools like MLflow, SageMaker, Airflow, or similar
  • Proficiency in Python and SQL; familiarity with Java or Spark is a plus
  • Experience with infrastructure-as-code (e.g., Terraform) and container orchestration (Kubernetes)
  • Familiarity with model monitoring, experimentation, and continuous training workflows
  • Bachelor's or Master’s degree in Computer Science, Engineering, or a related technical discipline

Nice to Have

  • Experience with GenAI deployment (Bedrock, LangChain, Claude, etc.)
  • Familiarity with vector databases (FAISS, Pinecone) and graph databases (Neo4j)
  • Exposure to A/B testing or online experimentation platforms
  • Understanding of privacy, security, and governance in ML deployments

Why Join Us?

We’re scaling a high-impact team to shape the future of monetization using AI. We welcome applicants who bring unique perspectives, even if you don’t check every box. Diverse teams lead to better ideas—and faster innovation.

#ZEOLife at Zuora

As an industry pioneer, our work is constantly evolving and challenging us in new ways that require us to think differently, iterate often and learn constantly—it’s exciting. Our people, whom we refer to as “ZEOs" are empowered to take on a mindset of ownership and make a bigger impact here. Our teams collaborate deeply, exchange different ideas openly and together we’re making what’s next possible for our customers, community and the world. 

As part of our commitment to building an inclusive, high-performance culture where ZEOs feel inspired, connected and valued, we support ZEOs with:

  • Competitive compensation, corporate bonus program and performance rewards, company equity and retirement programs
  • Medical insurance
  • Generous, flexible time off 
  • Paid holidays, “wellness” days and company wide end of year break
  • 6 months fully paid parental leave 
  • Learning & Development stipend
  • Opportunities to volunteer and give back, including charitable donation match
  • Free resources and support for your mental wellbeing  

Specific benefits offerings may vary by country and can be viewed in more detail during your interview process.

Location & Work Arrangements

Organizations and teams at Zuora are empowered to design efficient and flexible ways of working, being intentional about scheduling, communication, and collaboration strategies that help us achieve our best results. In our dynamic, globally distributed company, this means balancing flexibility and responsibility — flexibility to live our lives to the fullest, and responsibility to each other, to our customers, and to our shareholders. For most roles, we offer the flexibility to work both remotely and at Zuora offices.

Our Commitment to an Inclusive Workplace

Think, be and do you! At Zuora, different perspectives, experiences and contributions matter. Everyone counts. Zuora is proud to be an Equal Opportunity Employer committed to creating an inclusive environment for all.

Zuora does not discriminate on the basis of, and considers individuals seeking employment with Zuora without regards to, race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics.

We encourage candidates from all backgrounds to apply. Applicants in need of special assistance or accommodation during the interview process or in accessing our website may contact us by sending an email to assistance(at)zuora.com.

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Tags: A/B testing Airflow Angular APIs Athena AWS CI/CD Claude Computer Science Data quality Docker Engineering ETL FAISS Generative AI Java Kafka Kubernetes LangChain Machine Learning Microservices MLFlow ML infrastructure ML models MLOps Neo4j Node.js Pinecone Pipelines Privacy Python SageMaker Security Spark SQL Streamlit Terraform Testing

Perks/benefits: Career development Competitive pay Equity / stock options Flex hours Flex vacation Health care Insurance Medical leave Parental leave Salary bonus Startup environment Team events Wellness

Region: Asia/Pacific
Country: India

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