AI/ML Infrastructure Engineer

Minimum Requirements
 

• 3+ years of experience in leading the design and implementation of grid/cluster computing infrastructure with CPU and GPUs supporting AIML and NLP workloads.
• 3+ years of experience with Azure and/or GCP/GKE, as well as experience building complex infrastructure programmatically with IaC tools (Terraform/Ansible etc.)
• 1+ years of experience designing solutions and working with high-performance storage technologies including Object Storage.
• 2+ years of experience working and supporting network infrastructure for high throughput and low latency High performance (HPC) computing.
• 2+ years of experience with Elastic Search  
• 1+ years of working with big data (Big Query)
• Working knowledge and understanding of developing APIs using Python.
• Excellent understanding and working knowledge of cloud computing concepts like Virtual Private Cloud (VPC), landing zone, Identity and Access Management (IAM), App Service Environment, Blueprints, Control Plane etc.
• Excellent verbal, written, and interpersonal communication skills. Ability to articulate technical solutions to both technical and business audiences.
• Recent and demonstrated ability to influence management on technical or business solutions.
• Experience with CI/CD, DevOps concepts and SRE principles.

 
Preferred Skills

• 1+ years of experience in LLM, Generative AI (developing capabilities or dev/ops)
• Experience in developing APIs on GCP/Azure/API Gateways
• Experience with data processing technology (Apache Spark etc.)
• Experience with data virtualization technology (Tibco DV, Dremio, etc.)
• Understanding of Agile practices and ability to work with Agile teams to define and track user stories.
• Experience with designing and implementing complex F5 or other Load Balancer Technologies
• Knowledge and understanding of Cloud computing, PaaS design principles and micro services and k8s containers.
• Cloud certifications K8s, GCP & Azure preferred.