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1 week ago
We are seeking a seasoned AI Platform/Infrastructure Engineer to fill this challenging role. The ideal candidate will have extensive experience in building and deploying cloud-based solutions with a strong understanding of DevOps culture and infrastructure management.
Key Responsibilities:
- Design, build, and deploy scalable solutions in the cloud using Cloud Native or Cloud Agnostic approaches.
- Ensure seamless development and deployment processes from start to finish in a DevOps environment.
- Develop code, preferably in Python or Java.
- Implement Continuous Integration/Continuous Deployment (CI/CD) pipelines using tools like Github Actions or Jenkins.
- Manage Infrastructure as Code (IaC) using Terraform.
Required Skills and Experience:
- CI/CD: Experience with Github Actions or Jenkins
- Infrastructure as Code: Terraform
Focus Areas (One or more of the following):
- MLOps: ML Deployment and Model Serving with tools such as Kubeflow, KNative, KServe, Nvidia Triton, Ray Serve, MLflow, Sagemaker.
- Graph Databases: Experience with Graph Databases like Neo4J, JanusGraph, or DGraph (ingesting and consuming data).
- Big Data: Building Big Data pipelines or platforms to process petabytes of data, including experience with Lakehouse, Data Catalog, Data Lineage, Spark, Glue, and EMR.
- ML (Platform) Engineer: Experience building ML Platforms or ML Solutions.
Qualifications:
- 5+ years of experience in relevant fields (internships or personal projects not considered).
- Proficiency in coding, with a strong preference for Python or Java.
- Strong understanding and hands-on experience with DevOps practices.
- Expertise in cloud-native or cloud-agnostic solutions.
- Experience with infrastructure automation and tools like Terraform.
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