SRE - MLOps

Qualifications

• 6+ years of experience in ML Ops with strong knowledge in Kubernetes, Python, Mongo
  
  DB and AWS.
• Good understanding of Apache SOLR.
• Proficient with Linux administration.
• Knowledge of ML models and LLM.
• Ability to understand tools used by data scientists and experience with software development and test automation.
• Ability to design and implement cloud solutions and ability to build MLOps pipelines on cloud solutions (AWS).
• Experience working with cloud computing and database systems.
• Experience building custom integrations between cloud-based systems using APIs.
• Experience developing and maintaining ML systems built with open-source tools.
• Experience with MLOps Frameworks like Kubeflow, MLFlow, Data Robot, Airflow etc., experience with Docker and Kubernetes.
• Experience developing containers and Kubernetes in cloud computing environments.
• Familiarity with one or more data-oriented workflow orchestration frameworks (Kubeflow, Airflow, Argo, etc.).
• Ability to translate business needs to technical requirements.
• Strong understanding of software testing, benchmarking, and continuous integration.
• Exposure to machine learning methodology and best practices.
• Good communication skills and ability to work in a team.