onsite
GCP AI Engineer - NCS
AI Engineer
Lead end‑to‑end AI solutions on Google Cloud, designing and deploying machine learning models with Python and TensorFlow, while optimizing data pipelines and ensuring scalable, secure deployments on the Cloud AI Platform.
About the role
Key Responsibilities
- Design, develop, and deploy production‑ready machine learning models on Google Cloud Platform using TensorFlow and Vertex AI.
- Build and maintain robust data pipelines for training and inference, leveraging BigQuery, Cloud Storage, and Dataflow.
- Collaborate with data scientists and product teams to translate business requirements into scalable AI solutions.
- Implement model monitoring, logging, and automated retraining workflows to ensure high performance and reliability.
- Optimize model inference latency and cost through model compression, quantization, and efficient resource allocation.
Requirements
- 3+ years of experience in AI/ML engineering on GCP, with strong proficiency in Python and TensorFlow.
- Hands‑on experience with Vertex AI, Cloud AI Platform, and related GCP services (BigQuery, Dataflow, Pub/Sub).
- Solid understanding of data engineering concepts, ETL pipelines, and cloud architecture best practices.
- Experience with model versioning, CI/CD for ML, and monitoring tools such as Cloud Monitoring and Cloud Logging.
- Excellent problem‑solving skills and ability to work collaboratively in a fast‑paced environment.
Skills
machine learningpythontensorflow