Senior MLOps Engineer

Bachelor's degree in Computer Science, Engineering, or a related technical field. 5+ years of professional experience in MLOps, DevOps, or a senior Data Engineering role with a focus on operationalizing machine learning models. Expert-level proficiency in Python for pipeline automation and scripting. Extensive experience with the AWS SDK (Boto3) and Bash. Deep, hands-on experience with core AWS services, including S3, Lambda, SageMaker, IAM, and a solid understanding of networking within VPCs. Proven experience building and deploying containerized applications (Docker). Deep familiarity with Git workflows and experience implementing CI/CD pipelines. Demonstrated experience in designing and orchestrating complex, data-engineering-heavy pipelines.

Design, build, and own the end-to-end MLOps infrastructure on AWS. Implement and manage high-throughput, event-driven ML workflows. Develop and maintain robust CI/CD pipelines for model deployment. Orchestrate complex data pipelines for ingestion, processing, and updating embeddings in vector databases. Establish and manage systems for training phase management and experiment tracking. Implement comprehensive security measures. Collaborate with data science teams to translate prototypes into production-grade services.