MLOPs Engineer (Junior to Expert level) x4
Location: Hybrid (Mainly London based - ad-hoc on-site)
Duration: 6 months rolling
Rate: £400pd to £1200pd DOE (Negotiable - please tell us what you are looking for)

Overview:
Are you a seasoned MLOps Engineer with a passion for AI and a track record of deploying, monitoring, and maintaining of machine learning models in production environments for optimal performance? As an MLOps Engineer, youll play a critical role in shaping and delivering cutting-edge solutions that redefine industries and create transformative impact.

What You'll Do:
. Deploy and maintain machine learning models in production environments.
. Implement monitoring solutions to track model performance and detect anomalies.
. Collaborate with data scientists and engineers to streamline the model deployment process.
. Optimize models for scalability, reliability, and real-world performance.
. Implement and manage model versioning and rollback procedures.
. Troubleshoot and resolve issues related to model inference and data pipelines.
. Stay updated on the latest developments in MLOps and implement best practices for model life cycle management.

What You'll Bring:
. 5+ years of experience in MLOps or a related field.
. Masters or higher degree in Computer Science, Machine Learning, or a related field.
. Solid understanding of machine learning concepts and model deployment.
. Proficiency in programming languages such as Python.
. Experience with model deployment frameworks (eg, TensorFlow Serving, TorchServe).
. Knowledge of containerization and orchestration tools (eg, Docker, Kubernetes).
. Familiarity with monitoring and logging tools for MLOps.
. Strong collaboration and communication skills.