Senior MLOps Engineer

Experienced in production ML systems. Played a key role in building and operating large-scale machine learning infrastructure. Understand challenges of moving models from notebooks to production. Write clean, maintainable code. Understand software engineering best practices. Hands-on experience with containerisation. Hands-on experience with orchestration tools. Hands-on experience with CI/CD pipelines. Hands-on experience with infrastructure-as-code.

Build scalable ML infrastructure. Design, develop, and maintain MLOps platforms and pipelines. Collaborate with Data Scientists, ML Engineers, Software Engineers, Product and Platform teams. Implement CI/CD pipelines for ML models. Automate retraining workflows. Build monitoring systems. Solve ambiguous infrastructure problems. Evaluate new MLOps tools. Architect solutions for data science teams. Mentor engineers on MLOps best practices.