GCP AI/ML Engineer
On-siteChicago, Illinois, United States
Job Summary
Build and deploy production-grade machine learning pipelines using Vertex AI Pipelines and GCP-native services to automate data ingestion, feature engineering, and model training. Operationalize the end-to-end ML lifecycle by managing model deployment, monitoring, retraining, and versioning via robust CI/CD workflows. Integrate seamless data flows across BigQuery, Cloud Storage, and streaming sources while implementing governance frameworks for auditability and compliance. Collaborate with data scientists and engineers to translate business requirements into scalable, governed ML solutions, providing technical leadership on MLOps practices.
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or related field
- 4+ years of experience in machine learning engineering or MLOps
- Hands-on experience with Google Cloud Platform (GCP) services
- Vertex AI (Pipelines, Training, Endpoints)
- BigQuery
- Cloud Storage
- Strong programming skills in Python
- Experience building and deploying end-to-end ML pipelines
- Strong understanding of ML lifecycle and MLOps principles
Desired Qualifications
- Experience with TensorFlow, PyTorch, or Scikit-learn
- Familiarity with Kubeflow Pipelines or Apache Beam
- Experience with Docker and containerized deployments
- Knowledge of real-time ML inference and streaming architectures
- Hands-on experience with model monitoring tools and frameworks
- Understanding of feature stores and feature engineering pipelines
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