Machine Learning Platform Engineer

3 days ago

London, Greater London, United Kingdom Bazaarvoice Full time

We are seeking a highly skilled Machine Learning Platform Engineer to collaborate with our team at Bazaarvoice. You will work closely with engineers to create a platform utilizing vast amounts of data that will be leveraged by various products and systems within the company.

Key Responsibilities:
  • Design, Implement, and Maintain robust machine learning pipelines and tooling for both batch and streaming ML processes.
  • Develop and Manage monitoring and observability solutions for ML systems to ensure optimal performance and reliability.
  • Lead DevOps Practices, including CI/CD pipelines and Infrastructure as Code (IaC), to streamline ML system deployment and maintenance.
  • Architect and Implement cloud-based solutions on AWS to support scalable and efficient ML operations.
  • 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 and accuracy.
  • Participate in the Full ML Lifecycle, from data preparation to model deployment and monitoring.
  • Optimize and Refactor existing systems for improved performance and reliability.
Required Skills and Experience:
  • Strong Python Proficiency: Excellent skills for developing, deploying, and maintaining machine learning systems.
  • Language Versatility: Experience with statically-typed or JVM languages; willingness to learn Scala is highly desirable.
  • Cloud Engineering Skills: Extensive experience with Cloud Platforms & Services, ideally AWS (e.g., Lambda, ECS, ECR, CloudWatch, MSK, SNS, SQS).
  • Infrastructure as Code: Proficiency in IaC, particularly Terraform.
  • Kubernetes Expertise: Strong hands-on experience with managing clusters and deploying services.
  • Data Orchestration: Experience with ML orchestration tools (e.g., Flyte, Airflow, Kubeflow, Luigi, or Prefect).
  • CI/CD: Expertise in pipelines, especially GitHub Actions and Jenkins.
  • Networking: Knowledge of concepts and implementation.

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