MLOps Engineer

4 weeks ago

Cheadle, Staffordshire, United Kingdom Pets at Home Full time
Revolutionize Pet Care with MLOps

We're seeking a talented MLOps Engineer to join our Engineering team and collaborate closely with our Data Science division to build self-serve orchestration systems for model training, evaluation, and hosting in a multi-cloud environment.

Key Responsibilities:
  1. Deploy, monitor, and maintain machine learning models within GCP and Azure environments.
  2. Enhance model deployment pipelines using iterative, agile development practices, ensuring efficient model building, deployment, and maintenance.
  3. Integrate and optimize MLOps tools, templates, and processes to streamline our machine learning lifecycle and data operations.
  4. Manage model changes and deployments securely, efficiently, and reliably.
  5. Develop, maintain, and improve pipelines for model training, validation, and deployment.
  6. Proactively address issues related to model performance and data drift.
  7. Maintain comprehensive technical documentation for model deployment processes, versioning, and monitoring.
  8. Implement and manage robust testing frameworks for model validation and performance evaluation.
  9. Automate monitoring tools to track model performance, accuracy, and drift in real-time.
  10. Conduct code and model reviews and participate in knowledge-sharing sessions.
  11. Collaborate with DevOps to drive automation within CI/CD pipelines for machine learning workflows.
  12. Ensure that data used for model training and deployment meets the highest standards of quality and compliance.
  13. Uphold secure best practices across all aspects of the MLOps lifecycle.
Essential Experience, Knowledge & Expertise:
  1. Proven experience in managing and deploying machine learning models in production environments.
  2. Strong understanding of MLOps principles and best practices.
  3. Experience with ETL processes and data pipelines.
  4. Familiarity with containerization technologies (Docker) and version control systems (Git). Hands-on experience with major cloud platforms (GCP, AWS, Azure).
  5. Understanding of model evaluation metrics, performance monitoring, and data drift management.
Desirable Experience, Knowledge & Expertise:
  1. Experience with Vertex AI, Azure Machine Learning, or equivalent MLOps tools.
  2. Knowledge of agile methodologies such as Scrum or Kanban.
  3. Strong proficiency in a programming language such as Python and R.
  4. Experience creating cloud resources through infrastructure as code (Terraform/Terragrunt or similar).
  5. Familiarity with streaming data and real-time data processing.
  6. Experience deploying and/or using open-source MLOps frameworks and tools.
  7. Demonstrated ability to handle and troubleshoot real-world model deployment issues.
Role Specific Competencies:
  1. Product Mindset: Treat machine learning models and outputs as products, focusing on end-user impact and continuous improvement.
  2. Operational Excellence: Apply best practices in MLOps, including observability, monitoring, and maintaining SLAs.
  3. Agile Approach: Embrace iterative development and continuous feedback to refine and enhance machine learning workflows.
  4. Technical Excellence: Demonstrate a deep understanding of machine learning model training/outputs and deployment best practices.
Why Work with Us?
  1. Be part of a dynamic and innovative team revolutionizing the pet care industry.
  2. Work in a cutting-edge multi-cloud environment with opportunities for professional growth and development.
  3. Collaborate with a talented Data Science team on impactful projects.
  4. Enjoy a culture of continuous learning, innovation, and excellence.

We value and respect difference in all its forms and strive to reflect the diversity of the communities we operate in. If you're passionate about MLOps and eager to make an impact, we'd love to hear from you.

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