Data Infrastructure Engineer

We are seeking experienced Al Platform / Infrastructure Engineers to join our team. The ideal candidate will have 5+ years of relevant experience (excluding internships, prototypes, or personal projects) in building and deploying solutions with a strong understanding of DevOps culture and infrastructure management.

Key Responsibilities

• Design, build, and deploy solutions in the cloud, either Cloud Native or Cloud Agnostic
• Ensure seamless development and deployment processes from start to finish in a DevOps environment.
• Write code, preferably in Python or Java.
• Implement CI/CD pipelines using tools like Github Actions or Jenkins.
• Manage Infrastructure as Code (IaC) using Terraform.

Required Skills and Experience

• Cloud Experience: Cloud Native (Serverless): S3, Lambda, AWS Batch, ECS.
• Cloud Agnostic: Kubernetes services
• CI/CD: Experience with GitHub Actions or Jenkins
• Infrastructure as Code: Terraform

Focus Areas (One or more of the following)

1. MLOps: ML Deployment and Model Serving with tools such as Kubeflow, KNative, KServe, Nvidia Triton, Ray Serve, MLflow, and Sagemaker.
2. Graph Databases: Experience with Graph Databases like Neo4J, JanusGraph, or DGraph (ingesting and consuming data).
3. 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.
4. ML (Platform) Engineer: Experience building ML Platforms or ML Solutions.

Qualifications

• 5+ years of experience in relevant fields (internships or personal projects are 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.