Overall 10-12yrs and Minimum 5-7 years of hands-on experience developing GenAI/ML models and deploying them in a cloud environment.
Proficiency with Google Cloud Platform (GCP) and its AI/ML offerings (e.g., Vertex AI, BigQuery, Dataflow, Cloud Storage, Pub/Sub, Cloud Run, GKE).
Must have experience working with any agentic framework
Knowledge of Retrieval-Augmented Generation (RAG) concepts and processes
Strong software engineering skills: Python (primary), experience with ML frameworks (TensorFlow, PyTorch, scikit-learn), and API development (REST/GraphQL).
Experience designing and deploying microservices architectures and containerized solutions (Docker, Kubernetes; preference for GKE).
Solid experience in MLOps: model versioning, experiments, automated training, feature stores, model registries, monitoring, and governance.
Data processing and analytics expertise: SQL, data pipelines, ETL/ELT concepts, data quality, and data visualization support.