Machine Learning Performance Engineer

Through our expansive global network, product-passionate community & enterprise technology, we connect thousands of brands and retailers with billions of consumers. Our solutions enable brands to connect with consumers and collect valuable user-generated content, at an unprecedented scale. This content achieves global reach by leveraging our extensive and ever-expanding retail, social & search syndication network. And we make it easy for brands & retailers to gain valuable business insights from real-time consumer feedback with intuitive tools and dashboards. Brands and retailers struggle to make real connections with consumers. It's a challenge to deliver trustworthy and inspiring content in the moments that matter most during the discovery and purchase cycle. Time and money spent on content that doesn't attract new consumers, convert them, or earn their long-term loyalty. Our brand promise : closing the gap between brands and consumers. We are seeking an experienced ML Engineer to join our Machine Learning team and maintain continuity of our critical AI-powered services. This role combines hands-on model development with production system maintenance in a fast-paced, data-rich environment processing content at massive scale. Develop and enhance AI services including AI Insights pilot and AI Automated Answers using LLM/RAG architectures. Maintain and optimize our mission-critical Machine Moderation system using Python-based NLP models deployed on AWS (Lambda, ECS, SageMaker, SQS, SNS). Train, evaluate, and monitor machine learning models using orchestration tools (e.G. Manage ML pipelines on AWS with containerized services and CI/CD deployment via GitHub Actions. Implement streaming data processing using Kafka for real-time content moderation decisions. Monitor model performance and drift using observability tools (e.G. Arize AI). Collaborate with teams using Scala-based services and maintain API integrations for model serving. Conduct architectural reviews for ML pipeline design and Infrastructure as Code (Terraform). Research and implement novel LLM & NLP approaches for content moderation and consumer insights. Optimize batch and streaming ML workloads processing millions of reviews, questions, and answers daily. Strong Python proficiency for ML model development and deployment. Experience with AWS cloud services (Lambda, ECS, ECR, SageMaker, MSK, SNS, SQS). Familiarity with ML orchestration platforms and CI/CD pipelines. Knowledge of streaming technologies (Kafka) and high-volume data processing. Experience with NLP, LLMs, and production ML monitoring tools. Ideally with strong a Software Engineering or Computer Science background. Production ML system maintenance using cloud-native AWS infrastructure. Real-time and batch model serving with monitoring and alerting. Research and development of NLP applications for e-commerce content analysis. #Transparency and trust accelerate our collective performance. Passionate Pursuit of Performance Innovation over Imitation We seek to innovate as we are not content with the status quo. As a stronger company we build a stronger community. Commitment to diversity and inclusion Bazaarvoice provides equal employment opportunities (EEO) to all team members and applicants according to their experience, talent, and qualifications for the job without regard to race, color, national origin, religion, age, disability, sex (including pregnancy, gender stereotyping, and marital status), sexual orientation, gender identity, genetic information, military/veteran status, or any other category protected by federal, state, or local law in every location in which the company has facilities. Bazaarvoice believes that diversity and an inclusive company culture are key drivers of creativity, innovation and performance. Furthermore, a diverse workforce and the maintenance of an atmosphere that welcomes versatile perspectives will enhance our ability to fulfill our vision of creating the world’s smartest network of consumers, brands, and retailers. Candidates who are successful will be required to undergo a Basic level DBS (Disclosure and Barring Service) background check. #