Senior Machine Learning Engineer (GCP)

Tiger Analytics is looking for a skilled and innovative Machine Learning Engineer with hands-on experience in Google Cloud Platform (GCP) and Vertex AI to design, build, and deploy scalable ML solutions. You will play a key role in operationalizing machine learning models and driving the end-to-end ML lifecycle, from data ingestion to model serving and monitoring.

Key Responsibilities: • Develop, train, and optimize ML models using Vertex AI, including Vertex Pipelines, AutoML, and custom model training. • Design and build scalable ML pipelines for feature engineering, training, evaluation, and deployment. • Deploy models to production using Vertex AI endpoints and integrate with downstream applications or APIs. • Collaborate with data scientists, data engineers, and MLOps teams to enable reproducible and reliable ML workflows. • Monitor model performance and set up alerting, retraining triggers, and drift detection mechanisms. • Utilize GCP services such as BigQuery, Dataflow, Cloud Functions, Pub/Sub, and GCS in ML workflows. • Apply CI/CD principles to ML models using Vertex AI Pipelines, Cloud Build, and GitOps practices. • Implement model governance, versioning, explainability, and security best practices within Vertex AI. • Document architecture decisions, workflows, and model lifecycle clearly for internal stakeholders.