
Edge AI Solutions Engineer
7 days ago
We are seeking a skilled Edge AI Solutions Engineer to join our team. In this role, you will be responsible for designing and implementing AI solutions at the edge of networks. This involves integrating robust cloud infrastructure with machine learning models to enable real-time insights and monitoring.
Key Responsibilities:
- Design and implement AI solutions at the edge of networks.
- Develop and deploy machine learning models on OpenShift as REST APIs with real-time managed endpoints.
- Utilize Microsoft Azure ML for experimentation, model training, versioning, and lifecycle management.
- Configure private endpoints and security protocols for compliance and data protection.
- Work with Confluent Kafka for real-time streaming and event-driven architectures at the edge and cloud.
Infrastructure as Code:
Automate infrastructure provisioning using Terraform for consistent deployments across environments.
Observability:
Implement observability using Managed Prometheus, Grafana, Azure Application Insights, and AppInsights for edge health, performance, and usage metrics.
DevOps and MLOps:
Maintain CI/CD pipelines using Azure DevOps and ArgoCD for seamless model and infrastructure delivery. Monitor model performance post-deployment and handle model retraining as needed.
Requirements:
- 5 years of experience in ML/AI/DevOps engineering, including edge deployment.
- Strong proficiency in OpenShift, Azure ML, and Terraform.
- Hands-on experience with Kafka, Snowflake, and Function Apps.
- Proven experience with CI/CD pipelines, preferably Azure DevOps and Argo.
- Good understanding of monitoring tools, including Prometheus, Grafana, and AppInsights.
Benefits:
Our company prioritizes in-person collaboration while offering flexibility to support wellbeing, productivity, individual work styles, and life circumstances. We are committed to fostering an inclusive environment where everyone can thrive.
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