Description

Design, build, and deploy scalable machine learning models and AI applications on Google Cloud Platform using Vertex AI and GCP services.

This role is on-site.

Responsibilities

• Design and optimize ML pipelines for preprocessing, feature engineering, training, validation, and inference using Vertex AI.
• Fine-tune and deploy foundation models and LLM applications using Vertex AI Studio and Gemini APIs.
• Implement CI/CD pipelines for ML deployment, monitoring, experiment tracking, and drift detection.
• Containerize ML applications using Docker and deploy them via Kubernetes/GKE.
• Build and support ETL/ELT pipelines for structured and unstructured datasets using Spark.

Required Skills

• Strong experience with Vertex AI and Google Cloud Platform (GCP).
• Hands-on expertise in Python, TensorFlow, PyTorch, Scikit-learn, and XGBoost.
• Experience building and deploying scalable ML and AI applications.
• Knowledge of MLOps, CI/CD, model monitoring, and cloud-native deployment practices.
• Familiarity with LangChain and Generative AI/LLM applications.
• Understanding of monitoring and observability tools such as Prometheus and Cloud Monitoring.
• 5+ years of professional experience in software engineering or data science.
• Bachelor's or Master's degree in Computer Science or a related field.

Preferred Skills

• Experience with Docker, Kubernetes/GKE, and Terraform.

Key Skills

Education

Any Graduate