Staff MLOps Engineer

4 weeks ago

London, Greater London, United Kingdom Bazaarvoice Full time
About the Role

We're seeking a highly skilled Staff MLOps Engineer to join our Machine Learning team at Bazaarvoice. As a key member of our team, you'll play a crucial role in designing, implementing, and maintaining robust MLOps platforms and tooling for both batch and streaming ML pipelines.

Key Responsibilities
  • Design and implement cloud-based MLOps platforms and tooling for 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.
  • 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 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.
Required Skills and Experience
  • Strong Python proficiency for developing, deploying, and maintaining machine learning systems.
  • Experience with statically-typed or JVM languages, with a willingness to learn Scala.
  • Cloud engineering skills, with extensive experience with Cloud Platforms & Services, ideally AWS.
  • Infrastructure as Code (IaC) proficiency, particularly with Terraform.
  • Kubernetes expertise, with strong hands-on experience with managing clusters and deploying services.
  • Data orchestration experience, with knowledge of ML orchestration tools.
  • CI/CD expertise, with experience in pipelines, especially GitHub Actions and Jenkins.
  • Networking knowledge, with a focus on concepts and implementation.
  • Streaming experience, with familiarity with Kafka and other streaming technologies.
  • ML monitoring experience, with knowledge of observability tools.
  • NLP/LLMs experience, with a strong desire to learn.
  • CLI & shell scripting proficiency, with experience in scripting and command-line tools.
  • APIs experience, with knowledge of deploying and managing production APIs.
  • Software engineering best-practices knowledge, with a focus on industry standards and practices.
Preferred Qualifications
  • AWS AI Services experience, with hands-on experience with AWS SageMaker and/or AWS Bedrock.
  • Data processing experience, with knowledge of high-volume, unstructured data processing.
  • ML applications experience, with familiarity with NLP, Computer Vision, and traditional ML applications.
  • System migration experience, with previous work in refactoring and migrating complex systems.
  • AWS certification, with an AWS Solution Architect Professional or Associate certification.
  • Advanced degree, with a Master's degree in ML / AI / Computer Science.
Personal Qualities
  • Passion for building developer-friendly platforms and tools.
  • Thrives in a terminal-based development environment.
  • Enthusiasm for 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.

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