MLOps Engineer

MLOps Engineer

Hybrid working – 3 days in London

Permanent

As an MLOps Engineer, you will play a key role in optimizing, automating, and managing the deployment of machine learning models in production environments. You will work closely with data scientists, ML engineers, and DevOps teams to streamline the machine learning lifecycle, from development to deployment, monitoring, and scaling in the cloud. Your expertise will help us deliver robust, scalable, and efficient solutions for autonomous systems.

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.

Reach out at [email protected]