Staff MLOps Specialist

4 days ago


London, Greater London, United Kingdom Bazaarvoice Full time
Job Title

We are seeking a highly skilled Staff MLOps Specialist to join our Machine Learning team.


About the Role

This is a key member of the team responsible for designing and implementing robust MLOps platforms and tooling for both batch and streaming ML pipelines.

The successful candidate will have extensive experience with cloud-based solutions, particularly AWS, and a strong background in infrastructure as code, CI/CD pipelines, and containerization.

The role will involve collaborating with ML Engineers and Data Scientists to develop, train, and deploy machine learning models, as well as engaging in feature engineering and model optimization to improve ML system performance.


Responsibilities:
  1. Design and implement MLOps platforms and tooling for batch and streaming ML pipelines
  2. Develop and manage monitoring and observability solutions for ML systems
  3. Lead DevOps practices, including CI/CD pipelines and Infrastructure as Code (IaC)
  4. Collaborate with ML Engineers and Data Scientists to develop, train, and deploy machine learning models
  5. Engage in feature engineering and model optimization to improve ML system performance
  6. Participate in the full ML lifecycle, from data preparation to model deployment and monitoring
  7. Optimize and refactor existing systems for improved performance and reliability
  8. Drive technical initiatives and best practices in both MLOps and ML Engineering

Requirements:
  • 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
  • NLP/LLMs: Experience with NLP, LLMs, and RAG systems in production, or strong desire to learn
  • APIs: Experience with deploying and managing production APIs
  • Software Engineering Best-Practices: Knowledge of industry standards and practices

Benefits

We offer a comprehensive benefits package, including medical, dental, and vision insurance, 401(k) matching, and generous paid time off.


Location

The office is located in downtown Austin, within walking distance of many restaurants and bars.


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