AI/ML Engineer

Summary

Join Zuora's AIMS (AI, ML, and Science) 10X team as an AI/ML Engineer and help transform how the global economy monetizes through AI-powered systems. You will architect and build scalable AI and ML infrastructure, NLP pipelines, and real-time data solutions. Collaborate with data scientists, software engineers, and product managers to productionize AI solutions and deliver AI-native products impacting Zuora's revenue and customer growth. This role involves building scalable AI infrastructure, operationalizing AI solutions, developing NLP systems and GenAI integration, and building data engineering and feature pipelines. You will own end-to-end ML engineering and collaborate cross-functionally. The position requires a proven track record of deploying scalable AI solutions and expertise in distributed systems and cloud-native infrastructure.

Requirements

• 7+ years of experience in AI/ML engineering, NLP systems, or data engineering, with a proven track record of deploying scalable AI solutions in production
• Deep experience with distributed systems, real-time streaming platforms (e.g., Kafka), and cloud-native data/ML infrastructure (e.g., AWS S3, SageMaker, Bedrock, Lambda)
• Experience building NLP applications using traditional and transformer-based methods (e.g., spaCy, Hugging Face, LangChain, OpenAI)
• Proficiency in Python and/or Java, with strong fundamentals in software engineering and API design
• Expertise with orchestration frameworks (Airflow, Kubeflow) and model lifecycle tools (MLflow, SageMaker Pipelines, etc.)
• Solid understanding of data modeling, feature engineering, and data quality frameworks
• Experience with MLOps practices, CI/CD for ML, model monitoring, and performance tuning
• Comfortable working across structured and unstructured data, from relational databases to logs and documents
• Bachelor’s or Master’s in Computer Science, Engineering, Data Science, or a related technical field

Responsibilities

• Build Scalable AI Infrastructure: Design and develop robust data and ML pipelines that support both batch and real-time inference at scale using tools like Spark, Airflow, Kafka, and AWS
• Operationalize AI Solutions: Work closely with data scientists to take ML models from experimentation to production, integrating them into Zuora products with strong observability, reliability, and performance
• NLP Systems and GenAI Integration: Develop scalable NLP pipelines, implement LLM-based solutions using prompt engineering, retrieval-augmented generation (RAG), embeddings, and serve generative AI APIs in production
• Data Engineering and Feature Pipelines: Build and optimize ETL/ELT pipelines that transform raw transactional and behavioral data into structured, high-quality features for ML models and analytics
• Own End-to-End ML Engineering: From ingestion to deployment, monitor model drift, ensure model retraining, and implement CI/CD workflows for ML
• Collaborate Cross-Functionally: Partner with product, analytics, and science teams to understand business problems, propose scalable AI architectures, and translate prototypes into production-grade systems
• Drive Technical Excellence: Champion best practices in MLOps, data governance, model versioning, reproducibility, and responsible AI deployment

Preferred Qualifications

Familiarity with SaaS, eCommerce, pricing systems, or payments is a plus

Benefits

• Competitive compensation, variable bonus and performance reward opportunities, 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