Overview
On Site
Depends on Experience
Contract - Independent
Contract - W2
Contract - 12 Month(s)
Able to Provide Sponsorship
Skills
Python
Google Cloud Platform
Vertex AI
Vertex
MLOps
IAC
Docker
BigQuery
Job Details
Job Description:
- Lead the integration of machine learning models into business-critical applications using Google Cloud Platform Vertex AI.
- Collaborate with data engineers, data scientists, software engineers, and product owners to ensure seamless model deployment and performance in production environments.
- Design and implement scalable, resilient, and secure model inference pipelines using Vertex AI, Vertex Pipelines, and related services.
- Enable continuous delivery and monitoring of models via Vertex AI Model Registry, Prediction Endpoints, and Model Monitoring features.
- Optimize model serving performance, cost, and throughput under high-load, real-time, and batch scenarios.
- Automate model lifecycle management, including CI/CD pipelines, retraining, versioning, rollback, and shadow testing.
- Participate in architecture reviews and advocate best practices in ML model orchestration, resource tuning, and observability.
Required Skills:
- 2 years - Strong experience in model integration and deployment using Google Cloud Platform Vertex AI, especially around Vertex Pipelines, Endpoints, Model Monitoring, and Feature Store.
- Expertise in scaling ML models in production, including load balancing, latency optimization, A/B testing, and automated retraining pipelines.
- Proficiency in MLOps and model operationalization techniques, with knowledge of infrastructure-as-code and containerized environments.
Preferred Skills:
- Experience with MLOps tools such as Kubeflow, MLFlow, or TFX.
- Familiarity with enterprise monitoring tools like Prometheus, Grafana, or Stackdriver for ML observability.
- Exposure to hybrid or federated model deployment architectures.
Software Skills:
- Google Cloud Platform Vertex AI Suite (including Pipelines, Feature Store, Model Monitoring)
- Python (with emphasis on integration frameworks and automation)
- Git, Docker, Poetry, Terraform or Deployment Manager
- BigQuery, Dataflow, and Cloud Functions
- Monitoring tools (Stackdriver, Prometheus, etc.)
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.