MLOps Engineer

4 days ago

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

We are seeking a highly skilled MLOps Engineer to join our team at Osmii. As an MLOps Engineer, you will play a critical role in optimizing, automating, and managing the deployment of machine learning models in production environments.

**Key Responsibilities:**

  • Design, implement, and maintain scalable MLOps infrastructure to support the development and deployment of machine learning models.
  • Collaborate with data scientists and ML engineers to develop CI/CD pipelines for seamless model training, testing, and deployment.
  • Develop automation tools and scripts in Python for model training, tuning, and monitoring.
  • Ensure smooth deployment of models on Cloud Platforms (AWS, Azure, Google Cloud) and manage resources effectively.
  • Optimize model serving performance and scalability in cloud environments.
  • Implement model monitoring, logging, and alerting to ensure production systems are reliable and efficient.
  • Support end-to-end model lifecycle management, from development to production.
  • Apply best practices in CI/CD, infrastructure as code, and containerization (Docker, Kubernetes).
  • Work closely with cross-functional teams to ensure smooth operations and scaling of ML models used in Robotics and Autonomous Vehicles applications.

**Requirements:**

  • 3+ years of experience in MLOps, DevOps, or a related field.
  • Strong experience with Python and scripting for automation and integration with ML pipelines.
  • Expertise in deploying and managing machine learning models in TensorFlow.
  • Hands-on experience with CI/CD tools (e.g., Jenkins, GitLab CI, CircleCI) to automate model deployment.
  • Experience working with at least one Cloud Platform (AWS, Azure, GCP), with knowledge of cloud-based infrastructure management.
  • Solid understanding of containerization technologies like Docker and orchestration tools like Kubernetes.
  • Prior experience working in the Robotics or Autonomous Vehicle industry is mandatory.
  • Strong understanding of model serving frameworks, model versioning, and model performance monitoring in production.

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