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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Machine Learning Engineer - **Company:** Bazaarvoice, Inc. - **Location:** Belfast, UK - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Computer Vision, Command-Line Interface, Cloud Computing, Cloud Engineering, Continuous Integration, Data Cleansing, DevOps, Github, Integrated Development Environments, Java Virtual Machine (JVM), Python (Programming Language), Machine Learning, Shell Script, Software Engineering, Data Streaming, Unstructured Data, Data Processing, Scripting, Feature Engineering, Large Language Models, Grafana, Infrastructure as Code (IaC), AI Platforms, Kubernetes, Information Technology, Luigi, Apache Kafka, User Generated Content, Machine Learning Operations, Video Streaming, Cloudwatch, Amazon Simple Queue Service (SQS), Terraform, Code Restructuring, Data Pipelines, Jenkins - **Published:** August 25, 2026 - **Apply:** https://uk.indeed.com/viewjob?jk=854f0271d44ad26e ## About the Role * Strong Python Proficiency: Excellent skills for developing, deploying, and maintaining our machine learning systems. * Language Versatility: 5+ Years of Experience with statically-typed or JVM languages. Willingness to learn Scala is highly desirable. * Cloud Engineering Skills: 5+ years experience with Cloud Platforms & Services, ideally AWS (e.g., Lambda, ECS, ECR, CloudWatch, MSK, SNS, SQS). * Infrastructure as Code: 3+ Years Proficiency in IaC, particularly Terraform. * Kubernetes Expertise: 5+ years of hands-on experience with managing clusters and deploying services. * Data Orchestration: 5+ years of Experience with ML orchestration tools (e.g., Flyte, Airflow, Kubeflow, Luigi, or Prefect). * CI/CD: 5+ Years of Expertise in pipelines, especially GitHub Actions and Jenkins. * Networking: Knowledge of concepts and implementation. * Streaming: Experience with Kafka and other streaming technologies. * ML Monitoring: Familiarity with observability tools (e.g., Arize AI, Weights and Biases). * NLP/LLMs: Experience with NLP, LLMs, and RAG systems in production, or strong desire to learn. * CLI & Shell Scripting: Proficiency in scripting and command-line tools. * APIs: Experience with deploying and managing production APIs. * Software Engineering Best-Practices: Knowledge of industry standards and practices., * AWS AI Services: Hands-on experience with AWS SageMaker and/or AWS Bedrock. * Data Processing: Experience with high-volume, unstructured data processing. * ML Applications: Familiarity with NLP, Computer Vision, and traditional ML applications. * System Migration: Previous work in refactoring and migrating complex systems. * AWS Certification: AWS Solution Architect Professional or Associate certification. * Advanced Degree: Master's degree in ML / AI / Computer Science., * Passionate about building developer-friendly platforms and tools. * Thrives in a terminal-based development environment. * Enthusiastic about creating production-grade, robust, reliable, and performant systems. * Not afraid to dive into and improve complex existing solutions. * Team player who works well with ML Engineers, Data Scientists, and management. * Strong technical mentoring skills. * Excellent problem-solving and communication skills. ## Description You'll work closely with a team of engineers to create AI/ML solutions on top of our extensive syndication network data. These features will increase our Annual Recurring Revenue (ARR), reduce client churn, and make our Bazaarvoice User Generated Content (UGC) central to AI Shopping., * Design, implement, and maintain robust AI/ML solutions and tooling for both batch and streaming ML pipelines. * Develop and manage monitoring and observability solutions for ML systems. * Lead DevOps practices, including CI/CD pipelines and Infrastructure as Code (IaC). * Architect and implement cloud-based solutions on AWS (or similar public cloud providers). * Collaborate with ML Engineers and Data Scientists to develop, train, and deploy machine learning models. * Engage in feature engineering and model optimization to improve ML system performance. * Participate in the full AI/ML lifecycle, from data preparation to model deployment and monitoring. * Optimize and refactor existing systems for improved performance and reliability. * Drive technical initiatives and best practices in both MLOps and ML Engineering. ## Related Videos - [Machine Learning for Software Developers (and Knitters)](https://www.wearedevelopers.com/videos/154-machine-learning-for-software-developers-and-knitters) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Effective Machine Learning - Managing Complexity with MLOps](https://www.wearedevelopers.com/videos/185-effective-machine-learning-managing-complexity-with-mlops) - [Bringing AI Model Testing and Prompt Management to Your Codebase with GitHub Models](https://www.wearedevelopers.com/videos/1536-bringing-ai-model-testing-and-prompt-management-to-your-codebase-with-github-models) - [DevOps Maturity Check – a way to balance autonomy and alignment](https://www.wearedevelopers.com/videos/58-devops-maturity-check-a-way-to-balance-autonomy-and-alignment) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Why Upskilling And Reskilling is Important For Developers](https://www.wearedevelopers.com/magazine/428-why-upskilling-and-reskilling-is-important-for-developers)