******currently looking for candidates who are visa independent*****
Mandatory Skills:
Agentic AI/ADK/Python
Responsibilities:
- Data and Feature Pipelines: Design, build, and manage automated data ingestion, transformation, and validation pipelines using services like Kubeflow Pipelines and Vertex AI Pipelines.
- Feature Engineering: Implement and containerize feature engineering logic for diverse datasets, ensuring reusability and scalability.
- Data Validation: Integrate and manage data validation processes, including leveraging advanced techniques like AI Agents and the Generative Language API to automatically detect and remediate data quality issues.
- Model Training and Experimentation:
- Set up and maintain automated continuous training (CT) pipelines using Vertex AI Pipelines (Schedules) and Cloud Scheduler.
- Implement experiment tracking to log and compare model parameters, metrics, and artifacts.
- Configure and execute Hyperparameter Tuning jobs using Vertex AI Training to optimize model performance.
- Model Management: Establish a robust Model Versioning system to manage and store model artifacts securely in a centralized repository (Cloud Storage).
- Deployment and Serving:
- Containerize ML models and their dependencies using Docker and manage images with Artifact Registry.
- Build and maintain CI/CD workflows for ML models, ensuring seamless and automated deployment.
- Configure and manage low-latency production serving environments using Vertex AI Endpoints for real-time inference.
Qualifications:
- Strong experience with Google Cloud Platform (GCP) services, specifically in the MLOps and ML domain (Vertex AI, Kubeflow, Cloud Storage, Artifact Registry).
- Proven ability to design and implement end-to-end ML pipelines for data management, model training, and deployment.
- Hands-on experience with containerization technologies like Docker.
- Familiarity with CI/CD practices and pipeline automation.
- Knowledge of ML frameworks like TensorFlow, and experience with experiment tracking and hyperparameter tuning.
- Excellent problem-solving skills and a strong understanding of the ML lifecycle.
- Experience with the Generative Language API (Gemini model) or other AI Agent integrations is a plus.