Staff MLOps Engineer

4 weeks ago

Belfast, United Kingdom Bazaarvoice Full time

We're seeking a senior-level MLOps Engineer to lead the development and maintenance of our machine learning infrastructure. As a key member of the Machine Learning team, you'll work closely with engineers to create a scalable platform for ML model development and feature engineering.

Key Responsibilities:
  • Design, implement, and maintain robust 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.
Required Skills and Experience:
  • Strong Python Proficiency: Excellent skills for developing, deploying, and maintaining our 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.
  • 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.
Preferred Qualifications:
  • 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.
Personal Qualities:
  • 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.

This role is a key part of our Machine Learning team, and we're looking for someone who can help drive our MLOps capabilities forward.

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