Target Profile: 2 years of experience building and maintaining ML infrastructure or platforms in production environments. Demonstrated ability to take ML models from experimentation to deployment using MLOps best practices. Experience collaborating with data scientists, ML engineers, and backend teams on cross-functional projects. Technical Expertise: Proficiency in Python and core ML tooling (e.g., MLflow, Kubeflow, Airflow, Docker, Git). Familiarity with model training frameworks such as PyTo…