AI Infrastructure Engineer

AI Platform / Infrastructure Engineer:

5+ years of experience in relevant fields (internships, prototypes, and personal projects not

counted).

• Coding skills required (preferably Python or Java).
• Experience in DevOps culture (own developmentdeployment end-to-end).
• Experience in building or deploying solutions in the cloud, either:
• Cloud Native (Serverless): S3, Lambda, AWS Batch, ECS.
• Cloud Agnostic: Kubernetes services.
• CICD experience: GitHub Actions or Jenkins.
• Infrastructure as code: Terraform.
• Expertise in at least one of the following focus areas:
  
  MLOps: ML deployment and model serving (e.g., Kubeflow, KNative, KServe, Nvidia
• Triton, Ray Serve, MLflow, Sagemaker). Graph Databases: Ingesting and consuming data in graph databases such as Neo4J, JanusGraph, or DGraph.
• Big Data: Building big data pipelines/platforms to process petabytes of data
• (Kafka, Debizium, Lakehouse, Data Catalog, Data Lineage, Spark, Glue, EMR).
• ML (Platform) Engineering: Building ML platforms or ML solutions (Kafka,
• Sagemaker, KServe).
• Note: High preference for MLOps and Kafka expertise.